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Defining a conceptual framework for the integration of modelling and advanced imaging for improving the reliability and efficiency of bridge assessments

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Abstract

Current bridge inspection practices are typically predicated upon manual paper-based data collection methods, which significantly limit the ability to transfer knowledge gained throughout the lifecycle of the asset, to benefit the assessment of the inspector or engineer. This study aims to overcome the limitations of current practices and proposes a conceptual framework to improve the reliability and efficiency of current bridge asset management practices through the integration of Building Information Modeling (BIM) and advanced computing and imaging technologies. As a tool for bridge inspections, BIM offers significant potential when integrated with laser scanning and keypoint-based texture recognition, which allows for the detection of such defects as cracking, corrosion or settlement in bridge components. In recent years, the construction industry has seen an increased use of BIM technology on-site to aid the construction process. However, the applications of it are deficient through the asset management phases of a project. Given the ability of BIM to house all component specific information gathered from the construction, inspection and maintenance phases, BIM is envisioned to allow emphasis to be placed on retrieving the relevant information throughout the project lifecycle, ultimately enabling engineers and bridge inspectors to make more informed decisions about the current condition of the structure. Using BIM as the focal point for information collection throughout the project lifecycle, findings from advanced imaging and data processing are proposed to be stored within the model for recall at future bridge assessments.

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Acknowledgments

The authors wish to thank Shanghai Investigation Design & Research Institute Co., Ltd in China for providing the case study of the Yongxin Floodgate Project. The authors would like to additionally acknowledge the information provided by the Sydney Harbour Foreshore Authority for the Pyrmont Bridge BrIM project.

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Authors and Affiliations

  1. Griffith School of Engineering, Griffith University, Gold Coast, QLD, 4215, Australia

    Brodie Chan, Hong Guan & Lei Hou

  2. GHD Pty Ltd, Brisbane, QLD, 4000, Australia

    Brodie Chan

  3. School of Information and Communication Technology, Griffith University, Gold Coast, QLD, 4215, Australia

    Jun Jo

  4. School of Software, University of Technology Sydney, Sydney, NSW, 2007, Australia

    Michael Blumenstein

  5. Australasian Joint Research Centre for Building Information Modelling, Curtin University, Perth, WA, 6102, Australia

    Jun Wang

Authors
  1. Brodie Chan
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  2. Hong Guan
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  3. Lei Hou
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  4. Jun Jo
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  5. Michael Blumenstein
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  6. Jun Wang
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Correspondence to Hong Guan.

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Chan, B., Guan, H., Hou, L. et al. Defining a conceptual framework for the integration of modelling and advanced imaging for improving the reliability and efficiency of bridge assessments. J Civil Struct Health Monit 6, 703–714 (2016). https://doi.org/10.1007/s13349-016-0191-6

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  • DOI: https://doi.org/10.1007/s13349-016-0191-6

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