This present paper investigates the state of practice and research in damage information modeling for bridges. A dedicated information model, called damage information model, could provide a solution to improve the information exchange. The repeated digitalization is an error prone process and leads to redundant work.
#Saba cloud itrain registration
After damage registration or information exchange, the data is processed digitally. Current inspection on site is often done manually on paper, and paper is the medium to exchange condition information between involved stakeholders. Inspection and maintenance is essential to ensure the serviceability and safety of bridges. The Bridge collapse in Genoa let us take a closer look at the health state of bridges. Finally, the paper identifies the current research gaps, future directions obtained from the quantitative analysis, and in-depth discussions of the collected papers in this area. Moreover, based on the collected papers, application of TLS in bridge engineering and asset management was reviewed according to four categories including (1) generation of 3D model, (2) quality inspection, (3) structural assessment, and (4) bridge information modeling (BrIM).
Research trends, consisting of dominated sub-fields, co-occurrence of keywords, network of researchers and their institutions, along with the interaction of research networks, were quantitatively analyzed. Following the review, more than 1500 research publications were collected, investigated and analyzed through a twofold literature search published within the last decade from 2010 to 2020. This paper aims to provide a thorough mixed scientometric and state-of-the-art review on the application of terrestrial laser scanners (TLS) in bridge engineering and explore investigations and recommendations of researchers in this area. Advanced technologies, such as laser scanners, have become a suitable alternative for labor intensive, expensive, and unsafe traditional inspection and maintenance methods, which encourage the increasing use of this technology in construction industry, especially in bridges. Over the last decade, particular interest in using state-of-the-art emerging technologies for inspection, assessment, and management of civil infrastructures has remarkably increased. Challenges of implementing the proposed strategy are also discussed. The proposed strategy can be further extended for routine bridge inspection. Moreover, a knowledge-based system processes the data for generating recommendations for the bridge's safety condition and the retrofit strategy. Image data collected through high-quality camera mounted on UAV is uploaded to the Cloud, which is then leveraged by analytics engine for damage detection and representation, and generation of the post-earthquake bridge BIM. The existing bridge and its surrounding environment are digitalised by Geographic Information System (GIS) and BIM, from which geospatial data is extracted for generating optimum UAV's inspection route automatically by pre-defined algorithms. The framework is driven by various state-of-the-art digital technologies and consists of three main systems: route planning system, data collection and analysis system, and decision support system. This paper thereby proposes a systematic framework for post-earthquake bridge inspection using unmanned aerial vehicle (UAV) and 3D Building Information Modelling (BIM) reconstruction. To overcome this challenge, a rapid, intelligent and automated strategy for inspection of seismic damage to bridges is needed. Current damage assessment practices, however, are labour intensive, time consuming and subject to errors, which also raise safety concerns for those engineers undertaking the inspections. In the aftermath of major earthquakes, rapidly capturing and quantifying the extent and severity of damage on critical bridges play an important role in post-earthquake operations such as search and rescue, emergency repairs and long-term reconstruction.
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