Scholarlink

<p>Developing a comprehensive predictive framework for optimizing the bearing capacity of full-scale geosynthetic-reinforced foundations remains a challenge, as most prior studies relied on small-scale tests or simplified analyses that neglected key variable interactions. To address this research gap, a validated three-dimensional finite element model (FEM) was used to simulate a full-scale square footing on reinforced soil. A Central Composite Design was adopted to systematically vary eight design variables, including soil strength, footing geometry, and reinforcement configuration. The results were analyzed using Response Surface Methodology (RSM) and Analysis of Variance (ANOVA) to identify the most influential parameters and their interactions. The analysis showed that the soil friction angle was the dominant factor affecting bearing capacity, while reinforcement length and first-layer embedment depth were the most significant reinforcement-related parameters. A regression equation was developed, providing a practical predictive tool, and a multi-objective optimization identified an efficient design that maximized bearing capacity while minimizing reinforcement use. The combined FEM–RSM approach proved efficient in reducing experimental effort while offering reliable guidance for the design of geosynthetic-reinforced foundations.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Prediction and Optimization of Bearing Capacity for Shallow Foundations on Geosynthetic-Reinforced Soil Using Response Surface Methodology and Finite Element Modeling

  • 期刊论文

  • 发表日期：

    2025年10月14日

查看全文
  • Ali Farik,
  • Mohamed Djabri,
  • Mohamed Zohaïr Kaab,
  • Alaoua Bouaicha,
  • Abdelfattah Aouadj

摘要

Developing a comprehensive predictive framework for optimizing the bearing capacity of full-scale geosynthetic-reinforced foundations remains a challenge, as most prior studies relied on small-scale tests or simplified analyses that neglected key variable interactions. To address this research gap, a validated three-dimensional finite element model (FEM) was used to simulate a full-scale square footing on reinforced soil. A Central Composite Design was adopted to systematically vary eight design variables, including soil strength, footing geometry, and reinforcement configuration. The results were analyzed using Response Surface Methodology (RSM) and Analysis of Variance (ANOVA) to identify the most influential parameters and their interactions. The analysis showed that the soil friction angle was the dominant factor affecting bearing capacity, while reinforcement length and first-layer embedment depth were the most significant reinforcement-related parameters. A regression equation was developed, providing a practical predictive tool, and a multi-objective optimization identified an efficient design that maximized bearing capacity while minimizing reinforcement use. The combined FEM–RSM approach proved efficient in reducing experimental effort while offering reliable guidance for the design of geosynthetic-reinforced foundations.