人工神经网络在浅层地基减损性状承载力模拟中的应用

河南省核技术应用中心,郑州 450000

人工神经网络;岩体;浅层地基;减损性状;承载力数值模拟

Application of Artificial Neural Networks in Simulating the Bearing Capacity of Shallow Foundation Damage Characteristics
DING Junming,WANG Dawei,LIU Qiao'e,SHI Han

Henan Nuclear Technology Application Center, Zhengzhou 450000, China

Artificial neural network; Rock mass; Shallow foundation; Damage reducing characteristics; Bearing ca‐pacity numerical simulation

DOI: 10.13512/j.hndz.2026.05.15

备注

针对岩体上浅层地基在荷载作用下易产生不均匀沉降与减损行为的问题,提出了一种基于人工神经网络的承载力数值模拟方法。通过融合土工格栅与软粘土材料参数,将原始数据规范至有效区间,并构建基于人工神经网络的地基结构数值模型,建立了反映垫层、土工格栅与软黏土相互作用机制的岩体浅基仿真系统。数值模拟结果表明,当地面层刚度从210000MPa降至10MPa时,地基沉降量增加约28%,局部荷载作用下角点与作用点沉降差显著扩大,格栅应力随刚度降低而提高约35%,表明地基承载力性状与荷载类型、刚度参数密切相关。本研究实现了对不同工况下地基应力分布的高精度模拟与承载力定量评估,为岩土工程中沉降控制与结构优化提供了可靠依据,对提升地基工程安全性与耐久性具有重要实际意义。
To address the issue of uneven settlement and performance degradation of shallow foundations on rock masses under load, a numerical simulation method for bearing capacity based on artificial neural networks is pro‐posed. By integrating the parameters of geogrids and soft clay materials, the original data was normalized to an valid range, and a numerical model of the foundation structure based on an artificial neural network was constructed. The simulation system for shallow foundations in rock masses was established to reflect the interaction mechanisms among cushion layer, geogrids and soft clay. Numerical simulation results indicate that when the surface layer stiff‐ness decreases from 210 000 MPa to 10 MPa, foundation settlement increases by approximately 28%. Under local‐ized loading, the settlement difference between the corner points and loading center points significantly widens, and the stress in the geogrid increases by approximately 35% as stiffness decreases. This demonstrates that foundation bearing capacity characteristics are closely related to load type and stiffness parameters. This study achieves high-precision simulation of foundation stress distribution and quantitative assessment of bearing capacity under various working conditions, providing reliable basis for settlement control and structural optimization in geotechnical engi‐neering. It holds significant practical significance for enhancing the safety and durability of foundation engineering structures.
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