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    Estimation of the Ultimate Bearing Capacity of the Rocks via Utilization of the AI-Based Frameworks by Bianca Damico, Matteo Conti

    Published 2024-12-01
    “…The output of this study adds to the development in the area of geotechnical engineering by providing a sound methodology for Qu estimation in rock-socketed piles. …”
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    Article
  4. 324

    Analysis of Energy Dissipation Characteristics of Damaged Sandstone under Impact Load by Feng Wang, Haibo Wang, Ying Xu, Bing Cheng, Qianqian Wang

    Published 2021-01-01
    “…Before rock burst, coal, and gas outburst dynamic load, rock mass in geotechnical engineering has been an indifferent degree of damage. …”
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    Article
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    A Systematic Method to Evaluate the Shear Properties of Soil-Rock Mixture considering the Rock Size Effect by Minghui Ren, Guangsi Zhao, Xianhao Qiu, Qinghua Xue, Meiting Chen

    Published 2018-01-01
    “…The soil-rock mixture (S-RM) is widely applied in the geotechnical engineering due to its better mechanical properties. …”
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    Article
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    Predicting Optimum Moisture Content by the individual and hybrid approach of machine learning by Yinghui Yang, Yahui Dai, Qunting Yang

    Published 2025-01-01
    “…The Optimal Moisture Content (OMC) is the moisture level at which soil reaches its maximum density during compaction, making it vital in geotechnical engineering and construction for establishing the best conditions for soil strength and stability in infrastructure. …”
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    Article
  10. 330

    THE EFFECT OF SOIL NAILING INCLINATION FOR IMPROVEMENT OF GYPSUM SAND SOIL IN DIFFERENT SLOPES by Mustafa M. Abdalhusein, Yasir M. Al-Badran, Zuhair Abd Hacheem, Rusul H. Almahmodi, Mohammed S. Mahmood, Susan Mutar N. AlMihna

    Published 2024-09-01
    “…These findings offer valuable insights for improving slope stability in gypsum sand soils and contribute to the optimisation of soil nailing techniques in geotechnical engineering. …”
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    Article
  11. 331

    Local Stress Field Correction Method Based on a Genetic Algorithm and a BP Neural Network for In Situ Stress Field Inversion by Tianzhi Yao, Zuguo Mo, Li Qian, Jianhua He, Jianhai Zhang

    Published 2021-01-01
    “…The in situ stress field is the fundamental factor causing deformation and damage in geotechnical engineering, so it is the main basis for underground engineering design and excavation. …”
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    Article
  12. 332

    Staphylococcus Derived from Desert and Its Solidified Ability on Aeolian Sandy Soil by Yu Gao, De Yao, Cuiyan Wang, Yanxing Wang, Chi Li

    Published 2020-01-01
    “…It is a kind of mineralized bacteria seldom used in geotechnical engineering at present, and it was found to have good mineralization ability; the living conditions of Staphylococcus were optimized. …”
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    Article
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    Particle Flow Code Simulation of the Characteristics of Crack Evolution in Rock-Like Materials with Bent Cracks by Zhanguo Ma, Shixing Cheng, Peng Gong, Jun Hu, Yongheng Chen

    Published 2021-01-01
    “…The distribution and propagation of rock cracks have a significant impact on geotechnical engineering. Taking rock-like materials with bent cracks as the research object, the particle flow code in two dimensions numerical simulation method was used to study the impact of the bend number on rock-like materials strength and crack evolution. …”
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    Numerical Simulation on Non-Darcy Flow in a Single Rock Fracture Domain Inverted by Digital Images by Jianli Shao, Qi Zhang, Wenbin Sun, Zaiyong Wang, Xianxiang Zhu

    Published 2020-01-01
    “…The influence of rock seepage must be considered in geotechnical engineering, and understanding the fluid flow in rock fractures is of great concern in the seepage effect investigation. …”
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    Predictive Modeling and Experimental Analysis of Cyclic Shear Behavior in Sand–Fly Ash Mixtures by Özgür Yıldız, Ali Fırat Çabalar

    Published 2025-01-01
    “…The insights derived from this research underscore the potential of incorporating fly ash in sand mixtures for soil stabilization in geotechnical engineering. Furthermore, the integration of advanced machine learning techniques such as NARX models offers a powerful tool for predicting the behavior of soil mixtures, facilitating more effective and data-driven decision-making in geotechnical applications. …”
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    Article