Development of three-dimensional forward modeling and observation device for leakage electric field in the process of foundation pit pumping test - Yufeng Chen; Hui Chen; Jiayong Yan; Yuexin You; Suiming Liu (PLoS ONE, 2025)
Early detection of leakage in foundation pit retaining structures during excavation is critical for ensuring both construction safety and the integrity of adjacent buildings. Conventional surface direct current methods suffer from poor resolution, low interference to resistance, and limited capability in pinpointing leakage locations. To achieve accurate leakage identification and enhance the quality control of major engineering projects, this study first establishes a coupled electrokinetic-steady electric field response mechanism by integrating the naturally occurring electric field from electrokinetic effects in leakage zones with artificial steady electric fields during pumping tests. Fundamental governing equations were derived to characterize the leakage-induced electric field. Subsequently, a novel leakage detection system combining pumping tests with electric field measurements was developed. This system employs current injection through groundwater observation wells while monitoring surface potential distribution patterns during dewatering processes, enabling rapid localization of leakage points. A 3D finite element-infinite element coupled numerical model was established to perform forward modeling, systematically investigating the influences of leakage channel spatial distribution, and system parameters on electric field responses. Laboratory-scale physical model tests demonstrated that the proposed method significantly amplifies potential anomalies at leakage locations through pumping-induced groundwater flow. Results indicate that the integrated pumping-electric field detection system effectively reveals leakage-induced potential anomalies. The electrokinetic effect generated by groundwater movement through leakage channels during pumping operations substantially enhances detection signals, thereby improving both the accuracy and efficiency of leakage identification. This advancement provides a robust technical solution for quality assurance in deep excavation engineering.