Pullout resistance of biomimetic root-inspired foundation systems

Acta Geotechnica(2023)

引用 0|浏览0
暂无评分
摘要
Deep foundation and anchorage systems are often comprised of simple linear elements, limited by design, materials and techniques employed to build them. Their stability is attained by transferring structural loads to deeper, more stable soil layers across a larger area, reducing potential for excessive settlement and providing resistance against lateral forces from external factors including wind and earthquakes. In comparison, root systems distribute loads to a large volume of soil through a branched morphology of semiflexible elements. Roots also penetrate soil media, reduce erosion, create habitats, and exchange, store and transport resources, while continuously sensing and adapting to environmental conditions. Insights from their integration of multifunctionality can be transferred to civil engineering through biomimicry. As a first step toward designing root-inspired foundations, the effects of various morphological traits (laterals’ length, number of nodes, number of laterals, branching angle and laterals’ cross section) on foundation performance are evaluated through vertical pullout tests. Out of the model properties, general trends were observed, including the positive correlation between models’ surface area and maximum force reached. Yet, due to complex interactions between the model and granular media, no model property fully explained differences in pullout resistance of all models. The effects of each root trait on pullout resistance were analyzed separately, which can serve to adapt the design of root-inspired foundations and exploit granular physics principles. Potential reasons for surprising and counterintuitive results are also presented. Further studies could evaluate the assumptions given as potential explanations of these results by studying identified counterintuitive scenarios.
更多
查看译文
关键词
Biomimicry,Bio-inspired geotechnics,Biological roots,Branched foundations,Civil engineering,Pullout resistance
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要