岩土工程
结算(财务)
土-结构相互作用
结构工程
堆
地质学
工程类
土木工程
法律工程学
计算机科学
有限元法
万维网
付款
作者
Tuan A. Pham,Farshid Vahedifard
标识
DOI:10.1139/cgj-2025-0129
摘要
Energy piles are a dual-purpose geostructure system designed to serve both as load-bearing foundations and as a means of utilizing geothermal energy for heating and cooling buildings. Due to their dual function, the behavior of energy piles under temperature variation at the pile–soil interface is significantly more complex than that of traditional piles. This study proposes a unified method for predicting the load–settlement behavior of traditional and energy piles, formulated through a cubic equation that integrates end-bearing hardening, skin-friction softening, and a modified effective stress theory accounting for particle contact area evolution. Unlike existing approaches, the proposed method uniquely separates end-bearing and skin-friction resistances and captures the coupled thermal-mechanical effects at the soil–pile interface, including both resistance gains and losses due to heating or cooling. Validation against interface shear tests and full-scale field measurements confirms the accuracy and robustness of the proposed method. Results show that the proposed framework significantly improves load–settlement predictions and provides a physically consistent and practical tool for energy pile design under varying thermal and mechanical loads. The findings also highlight that temperature effects on energy pile resistance vary with soil conditions. Heating can increase resistance via pile expansion, radial thermal stress, higher particle contact, and friction angle. Conversely, it may reduce resistance due to thermally induced excess pore-water pressure, lower overconsolidation, total stress reduction, decreased stiffness, and cohesion loss. These opposing mechanisms highlight the complex, site-specific thermomechanical behavior of energy piles. Considering microstructural evolution and thermal-softening effects is necessary to enhance the predictive capabilities for pile performance in complex operational environments.
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