Post-earthquake operations, such as search and rescue and damage assessment, require efficient and effective surveying technologies to rapidly capture the “as-damaged” state of buildings. Recent research has shown early feasibility of methods for compilation of as-damaged building information models (BIM) from as-damaged point cloud data and “as-built” models. Yet research efforts to develop and rigorously test appropriate methods are seriously hampered by the obvious scarcity of access for researchers to earthquake-damaged buildings for surveying specimens and hence the lack of terrestrial laser scanning data of post-earthquake buildings. Full-scale or reduced-scale physical models of building components can be built and damaged using a shaking table or other structural laboratory equipment, and these can be scanned, all at reasonable cost. However, equivalent full-scale building samples are unavailable. The solution is to synthesize accurate and representative data sets. A computational approach for compiling such data sets, including BIM modeling of damaged buildings and synthetic scan generation, is proposed. The approach was validated experimentally through compilation of two full-scale models of buildings damaged in earthquakes in Turkey.
|Journal||Journal of Computing in Civil Engineering|
|Publication status||Published - 1 May 2016|