• Journal of the Computational Structural Engineering Institute of Korea
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• v.37 no.1
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• pp.33-40
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• 2024

The volume of shells, a prominent form of marine waste, is steadily increasing each year. However, a significant portion of these shells is either discarded or left near coastlines, posing environmental and social concerns. Utilizing shells as a substitute for traditional aggregates presents a potential solution, especially considering the diminishing availability of natural aggregates. This approach could effectively reduce transportation logistics costs, thereby promoting resource recycling. In this study, we explore the feasibility of employing wasted shell aggregates in 3D concrete printing technology for marine structures. Despite the advantages, it is observed that 3D printing concrete with wasted shells as aggregates results in lower strength compared to ordinary concrete, attributed to pores at the interface of shells and cement paste. Microstructure characterization becomes essential for evaluating mechanical properties. We conduct an analysis of the mechanical properties and microstructure of 3D printing concrete specimens incorporating wasted shells. Additionally, a mix design is proposed, taking into account flowability, extrudability, and buildability. To assess mechanical properties, compression and bonding strength specimens are fabricated using a 3D printer, and subsequent strength tests are conducted. Microstructure characteristics are analyzed through scanning electron microscope tests, providing high-resolution images. A histogram-based segmentation method is applied to segment pores, and porosity is compared based on the type of wasted shell. Pore characteristics are quantified using a probability function, establishing a correlation between the mechanical properties and microstructure characteristics of the specimens according to the type of wasted shell.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.5
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• pp.619-628
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• 2009

LiDAR has capability of rapid data acquisition and provides useful information for reconstructing surface of the Earth. However, Extracting information from LiDAR data is not easy task because LiDAR data consist of irregularly distributed point clouds of 3D coordinates and lack of semantic and visual information. This thesis proposed methods for automatic extraction of buildings and 3D detail modeling using airborne LiDAR data. As for preprocessing, noise and unnecessary data were removed by iterative surface fitting and then classification of ground and non-ground data was performed by analyzing histogram. Footprints of the buildings were extracted by tracing points on the building boundaries. The refined footprints were obtained by regularization based on the building hypothesis. The accuracy of building footprints were evaluated by comparing with 1:1,000 digital vector maps. The horizontal RMSE was 0.56m for test areas. Finally, a method of 3D modeling of roof superstructure was developed. Statistical and geometric information of the LiDAR data on building roof were analyzed to segment data and to determine roof shape. The superstructures on the roof were modeled by 3D analytical functions that were derived by least square method. The accuracy of the 3D modeling was estimated using simulation data. The RMSEs were 0.91m, 1.43m, 1.85m and 1.97m for flat, sloped, arch and dome shapes, respectively. The methods developed in study show that the automation of 3D building modeling process was effectively performed.