Pipe-jacking is a construction method widely used in pipeline constructions. Prediction of ground deformation induced by pipe-jacking, is important for safety and scheduling purposes. This paper presents an approach to predict ground deformation during pipe-jacking considering following factors: (i) bulkhead additive thrust; (ii) friction on jacking machine; (iii) grouting pressure; and (iv) ground loss. Mindlin’s solution was used to calculate the ground deformation induced by bulkhead additive thrust and friction on the jacking machine. The shearing disturbance coefficient was adopted to evaluate the mitigation effect of shearing behavior on ground deformation. Verruijt’s solution was used to simulate the effect of grouting pressure. Sagaseta’s method was adopted to consider the ground loss induced by over-excavation. Subsequently, a three-dimensional analytical solution for ground deformation induced by pipe-jacking was obtained. A case study based on a pipe-jacking project undertaken in Jiangsu, China was analyzed to validate the proposed approach. The results indicated that the proposed approach was robust and could be implemented for future pipe-jacking projects.

Structural monitoring and engineering surveys that use the Global Positioning System (GPS) have traditionally performed using a so-called carrier-phase double-difference method in data processing. The method requires at least one reference GPS station to be continuously operated in the field during the monitoring period. The stability and data quality of the reference station would directly affect the accuracy of displacement measurements at the rover station. Furthermore, it becomes increasingly difficult to maintain “ideal” reference stations in urban environments. This article introduces a method for using stand-alone GPS units to conduct millimeter-accuracy structural deformation monitoring for poststudy or for near real-time structural health monitoring. Two years of continuous GPS observations obtained from two high-rise buildings in Beijing were used to depict the detailed method. The method comprises three steps: (1) solving GPS antenna positions with respect to a global reference frame (IGS08), (2) establishing a stable local reference frame and transforming the global positions into the local reference frame, and (3) deriving a regional seasonal model and correcting GPS-derived positional time series with the regional model. It is concluded that 2- to 3-mm horizontal accuracy and 5- to 7-mm vertical accuracy can be achieved for daily solutions with the proposed method in the Beijing metropolitan area. The key products from this study are the Stable Beijing Reference Frame (SBJRF) and the local seasonal model for GPS-derived (vertical) positional time series. SBJRF will be incrementally improved and periodically updated to synchronize with the update of the IGS reference frame. The general theory and method presented in this article could be applied to other urban areas for conducting structural health monitoring in near real time.