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Inserting a prestressed high-intensity concrete pipe pile into a cement–soil mixing pile can form a new composite pile named the composite foundation with stiffened deep cement mixing (SDCM) pile. The Huanghuai alluvial stratum in China is selected to carry out the in situ test for the SDCM pile, and the bearing capacity of the SDCM pile is tested by the slow-speed maintenance load method. The results show that for an SDCM pile with dense silt and fine sand as the bearing layer, the characteristic value of bearing capacity can reach 2,300 kN, which means an SDCM pile with a length of 8.0 m meets the load requirement of a general high-rise building. Further analysis shows that the SDCM pile saves more than 40% of the cost compared with the traditional CFG pile and has better quality control advantages at the same time. This research can provide basic data and design references for similar site foundation projects.

The current expansion of building structures has created a demand for efficient and smart surface quality evaluation at the acceptance phase. However, the conventional approach mainly relies on manual work, which is labor-intensive, time-consuming, and unrepeatable. This study presents a systematic and practical solution for surface quality evaluation of indoor building elements during the acceptance phase using point cloud. The practical indoor scanning parameters determination procedure was proposed by analyzing the project requirements, room environment, and apparatus. An improved DBSCAN algorithm was developed by introducing a plane validation and coplanar checking to facilitate the surface segmentation from the point cloud. And a revised Least Median of Square-based algorithm was proposed to identify the best-fit plane. Afterwards, the flatness, verticality, and squareness were evaluated and depicted using a color-coded map based on the segmented point cloud. The experiment on an apartment showcases how the system improves the information flow and accuracy during building acceptance, resulting in a potentially smart acceptance activity. [ABSTRACT FROM AUTHOR]