Accurate estimation of concrete (including shotcrete) consumption plays a crucial role in tunnel construction. A novel method has been introduced to accurately estimate concrete consumption with terrestrial laser scanning (TLS). The estimation needs to capture TLS data of tunnel surfaces at different stages of construction. Unrolling point clouds, a novel two-stage algorithm consisting of noise removal and hole filling has been used to generate resampled points. Furthermore, resampled points from two scans (before and after lining construction) ultimately generate an innovative computation model composed of multiple hexahedral elements, which is used for calculating volumes. The proposed technique was applied to the Tiantaishan highway tunnel and Da Fang Shan high-speed railway tunnel. The calculation relative error of the rebound rate is 0.19%, and the average relative error in predicting the demand for secondary lining concrete is 0.15%. Compared with 3D Delaunay with curve fitting, the proposed technique offers a more straightforward operation and higher accuracy. Considering factors such as tunnel geometry, support design, and concrete properties, a computational model will provide valuable insights into optimizing resource allocation and reducing material waste during construction.
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