After an earthquake, Terrestrial Laser Scanning (TLS) can capture point clouds of the damaged state of building facades rapidly, remotely and accurately. A long-term research effort aims to develop applications that can reconstruct 'as-damaged' BIM models of reinforced concrete (RC) framed buildings based on their 'as-built' BIM models and scans of their 'as-damaged' states. This paper focuses on a crucial step: generating an initial 'best-guess' for the new locations of the façade structural members. The output serves as the seed for a recursive process in which the location and damage to each object is refined in turn. Locating the 'as-built' structural members in the 'as-damaged' scan is challenging because each member may have different displacement and damage. An algorithm was developed and tested for the case of reinforced concrete frames with masonry infill walls. It exploits the topology of the frames to map the original structural grid onto the damaged façade. The tests used synthetic datasets prepared from records of two earthquake-damaged buildings. In both cases, the results were sufficiently accurate to allow progress to the following step, assessment of the individual structural members.

Accurate and reliable information about buildings can greatly improve postearthquake responses, such as search and rescue, repair and recovery. Building Information Modeling (BIM), rapid scanning and other assessment technologies offer the opportunity not only to retrieve as-built information but also to compile as-damaged models. This research proposes an information model to facilitate the data flow for post-earthquake assessment of reinforced concrete structures. The schema development was based on typical damage modes and the existing Industry Foundation Class (IFC) schema. Two examples of damaged structures from recent earthquake events, compiled using an experimental damage modeling software, illustrate the use of the data model. The model introduces two new classes, one to represent segments of building elements and the other to model the relationships between segments and cracks. A unique feature is the ability to model the process of damage with a binary tree structure. Methods for exporting asdamaged instance models using IFC are also discussed.

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-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.

The potential for automated construction quality inspection, construction progress tracking and post-earthquake damage assessment drives research in interpretation of remote sensing data and compilation of semantic models of buildings in different states. However, research efforts are often hampered by a lack of full-scale datasets. This is particularly the case for earthquake damage assessment research, where acquisition of scans is restricted by scarcity of access to post-earthquake sites. To solve this problem, we have developed a procedure for compiling digital specimens in both pre-and post-event states and for generating synthetic data equivalent to which would result from laser scanning in the field. The procedure is validated by comparing the physical and synthetic scans of a damaged beam. Interpretation of the beam damage from the synthetic data demonstrates the feasibility of using this procedure to replace physical specimens with digital models for experimentation and for other civil engineering applications.