Crack-Informed Structural Modelling and Assessment of Existing Concrete Infrastructure

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Civil infrastructure in Canada, such as the Ville-Marie tunnel (Montreal) and the Gardiner Expressway (Toronto), cause economic disruptions and pose undue safety risks as they deteriorate at rates exceeding our ability to replace them. For reinforced concrete (RC) construction, structure health is typically assessed in a qualitative manner using visual benchmarks such as concrete crack lengths, widths, and patterns in combination with condition-rating criteria to classify damage. However, accurately inferring distress severity from visual RC cracking is extremely challenging, requiring consideration of structure and damage details that are typically ignored in the assessment process. To ensure that the limited resources available for managing the nation's built environment are directed where they are needed most, significant research is required to enable reliable RC structural assessments. This means new damage inspection technologies, innovative and capable decision making tools, and novel modelling procedures that utilize observable damage. The long-term goal of this research program is to develop inspection methods that can accurately characterize discernible concrete damage in built RC infrastructure, and tools that employ inspection data to enable reliable damage-based structural assessments. The application areas for these technologies are widespread and, in industries that already employ infrastructure inspections, are highly-conducive to future adoption and implementation. Through the next five years my team will: 1) explore the role of image-based analysis techniques for establishing field-conducive methods of extracting crack feature response data from RC infrastructure, 2) fill key data gaps that are impeding the development of advanced crack-based assessment procedures through the performance of targeted testing activities involving field-representative RC components, and 3) define innovative alternatives to the current state-of-the-art in the assessment of damaged RC infrastructure through the development of crack-based nonlinear finite element analysis techniques and assessment tools that employ discernible concrete cracking features as input. Image-based crack measurement techniques have the potential to significantly advance traditional RC structure inspection methods by providing better resolution monitoring, extracting crack feature data not currently obtained, and removing subjectivity from the process. The modelling tools developed through this research will help ensure that the management of ageing infrastructure, a growing challenge that Canadian engineers are now facing regularly, is done using reliable assessment techniques. This timely research will provide original and impactful structural assessment technologies, and HQP with directly relevant skillsets, to ensure that built structures in Canada exhibiting severe distress are identified, and that resources for infrastructure maintenance are optimally allocated.