Information modeling of earthquake-damaged reinforced concrete structures

Accurate and reliable information about buildings can greatly improve post-earthquake 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 as-damaged instance models using IFC are also discussed

A Computational Procedure for Generating Specimens of BIM and Point Cloud Data for Building Change Detection

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

Towards generation of as-damaged BIM models using laser-scanning and as-built BIM: First estimate of as-damaged locations of reinforced concrete frame members in masonry infill structures

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

Semantic Enrichment for Building Information Modeling: Procedure for Compiling Inference Rules and Operators for Complex Geometry

Semantic enrichment of building models adds meaningful domain-specific or application-specific information to a digital building model. It is applicable to solving interoperability problems and to compilation of models from point cloud data. The SeeBIM (Semantic Enrichment Engine for BIM) prototype software encapsulates domain expert knowledge in computer readable rules for inference of object types, identity and aggregation of systems. However, it is limited to axis-aligned bounding box geometry and the adequacy of its rule-sets cannot be guaranteed. This paper solves these drawbacks by (1) devising a new procedure for compiling inference rule sets that are known a priori to be adequate for complete and thorough classification of model objects, and (2) enhancing the operators to compute complex geometry and enable precise topological rule processing. The procedure for compiling adequate rule sets is illustrated using a synthetic concrete highway bridge model. A real-world highway bridge model, with 333 components of 13 different types and compiled from a laser scanned point cloud, is used to validate the approach and test the enhanced SeeBIM system. All of the elements are classified correctly, demonstrating the efficacy of the approach to semantic enrichment

Information modeling of earthquake-damaged reinforced concrete structures

Accurate and reliable information about buildings can greatly improve post-earthquake 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 as-damaged instance models using IFC are also discussed

A Computational Procedure for Generating Specimens of BIM and Point Cloud Data for Building Change Detection

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

Towards generation of as-damaged BIM models using laser-scanning and as-built BIM: First estimate of as-damaged locations of reinforced concrete frame members in masonry infill structures

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 member

Preparation of Synthetic As-Damaged Models for Post-Earthquake BIM Reconstruction Research

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 Turke