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Advancements and development trend in statistical damage constitutive models for rock: a comprehensive review

Author

Listed:
  • Wei Liu

    (Jilin University)

  • Shangxian Yin

    (North China Institute of Science and Technology)

  • Hung Vo Thanh

    (Van Lang University
    Middle East University)

  • Mohamad Reza Soltanian

    (University of Cincinnati)

  • Qingyang Yu

    (Jilin University)

  • Songlin Yang

    (Jilin University)

  • Yarui Li

    (Jilin University)

  • Zhenxue Dai

    (Jilin University
    Jilin University)

Abstract

This paper provides a comprehensive exploration of the research progress in the field of rock statistical damage constitutive models. The introduction section highlights the significance and necessity of this research by discussing the background and importance of the rock statistical damage constitutive models. The damage mechanics section lays the foundation for the subsequent discussions by defining damage, examining observation and measurement methods, and introducing damage variables. The section on rock micro-elements failure criteria compares and analyzes various criteria, assessing their advantages, disadvantages, and suitability. This analysis provides a basis for subsequent modeling efforts. The paper then discusses the statistical distribution of rock micro-elements. It explores their properties, applicability, and usage in rock statistical damage constitutive models, guiding researchers in selecting appropriate distributions. The rock damage models section explains the mechanism and essence of rock damage, as well as various modification methods to enhance the accuracy and applicability of the models. In the rock statistical damage constitutive models section, several models based on Weibull, entropy, normal, and logarithmic normal distributions are elaborated. The advantages, disadvantages, applicability ranges, and improvement directions of each model are discussed in detail. The concluding section summarizes the current state of research and suggests future avenues for the development of rock statistical damage constitutive models. It emphasizes the need to enhance the predictive capability, accuracy, and applicability of these models in practical scenarios. Statistical damage constitutive models for rock are valuable tools for predicting the mechanical behavior of rock structures.

Suggested Citation

  • Wei Liu & Shangxian Yin & Hung Vo Thanh & Mohamad Reza Soltanian & Qingyang Yu & Songlin Yang & Yarui Li & Zhenxue Dai, 2025. "Advancements and development trend in statistical damage constitutive models for rock: a comprehensive review," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 121(4), pages 3703-3744, March.
  • Handle: RePEc:spr:nathaz:v:121:y:2025:i:4:d:10.1007_s11069-024-06967-6
    DOI: 10.1007/s11069-024-06967-6
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    References listed on IDEAS

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    1. Guijie Zhao & Chen Chen & Huan Yan, 2019. "A Thermal Damage Constitutive Model for Oil Shale Based on Weibull Statistical Theory," Mathematical Problems in Engineering, Hindawi, vol. 2019, pages 1-11, October.
    2. Muhammad Ali & Enyuan Wang & Zhonghui Li & Xiaoran Wang & Naseer Muhammad Khan & Zesheng Zang & Saad S. Alarifi & Yewuhalashet Fissha, 2023. "Analytical Damage Model for Predicting Coal Failure Stresses by Utilizing Acoustic Emission," Sustainability, MDPI, vol. 15(2), pages 1-18, January.
    3. Dongxu Liang & Nong Zhang & Lixiang Xie & Guangming Zhao & Deyu Qian, 2019. "Damage and fractal evolution trends of sandstones under constant-amplitude and tiered cyclic loading and unloading based on acoustic emission," International Journal of Distributed Sensor Networks, , vol. 15(7), pages 15501477198, July.
    4. Lingjie Zhu & Xiaoli Xu & Xiaojian Cao & Shaoyong Chen, 2019. "Statistical Constitutive Model of Thermal Damage for Deep Rock considering Initial Compaction Stage and Residual Strength," Mathematical Problems in Engineering, Hindawi, vol. 2019, pages 1-10, July.
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