Date of Award

Winter 2-2015

Embargo Period


Degree Type


Degree Name

Doctor of Philosophy (PhD)


Civil and Environmental Engineering


Burcu Aki

Second Advisor

James H. Garrett

Third Advisor

Ozgur Kurc


Objective, accurate, and fast assessment of damage to buildings after an earthquake is crucial for timely remediation of material losses and safety of occupants of buildings. Currently, visual inspection of buildings for damage and manual identification of damage severity are the primary evaluation methods. However, visual inspections have a number of shortcomings. In different research studies, visual observations and inspector judgment have been shown to differ amongst different inspectors in terms of thoroughness and reliability of inspection, details included in inspection reports, and results of the damage assessment. Automatic damage assessment could help in evaluating damaged buildings by reducing the dependency on subjective data collection and evaluation of the damage observations. Laser scanning is a promising tool for field data collection for post-earthquake damage assessment as laser scanners are able to produce accurate and dense 3D measurements of the environment. Laser scan data can be processed to extract damage indicators. Identifying the damage severity requires the damage indicators be related to the building components in 3D space, as well as the structural configuration of the building, details of the reinforcement, and actual material properties. A Building Information Model (BIM) within which a structural system and damage are represented can serve as the underlying information source for damage assessment and post-earthquake seismic performance evaluation. However, further research is required for utilizing laser scan data and as-is BIMs generated from laser scan data for storing and reasoning about damaged buildings. In order to address the challenges and needs stated above, (1) the unique characteristics of laser scan data, which can potentially limit the reliability of the scanner data for crack identification under certain scenarios were investigated; (2) the information requirements for representing and reasoning about damage conditions were formalized; (3) a representation schema for damaged conditions was developed; and (4) reasoning mechanisms were studied for identifying the damage modes and severities of components using the identified damage parameters and structural properties. The research methods involved experiments to identify the characteristics of laser scanners for damage detection, investigation of damage assessment guidelines, and investigation and analysis of Building Information Modeling standards. The results of the investigation on damage assessment standards were used for identifying the information requirements for the representation of damage and for developing the representation schema. Validation studies include: (1) validation of the information requirements by an analysis to quantify the sensitivity of damage assessment to the identified damage parameters; (2) validation of generality of the representation schema to masonry components; (3) validation of the reasoning mechanisms with a user study. The contributions include: (1) characterization of two laser scanner for detecting earthquake induced cracks; (2) identification of information requirements for visual assessment of earthquake damage on reinforced concrete shear walls; (3) a schema for representing the earthquake damage for supporting the visual assessment; and (4) approach for identifying the damage mode and severity of reinforced concrete walls.