4D Digital Integration for Nanomaterial-Based Monitoring and Treatment of Bridge Piers Defects

This study presents an innovative 4D digital model that integrates Bridge Information Modeling (BrIM) with several types of data to defect detection in complex bridge structures. The model promotes precise data preparation, navigation, visualization, integration, and monitoring, enabling the identification of defects, like material deterioration, condition changes, and structural clashes in components like trusses. Bridge model provides time-based access to maps, allowing users to explore changes over time and predict future conditions. The integration of time dimension into the 4D model provides dynamic tools for exploring changes over time, allowing for analysis and maintenance planning. Through the use of advanced 4D simulation technology, the study’s effectiveness is in visualizing workflows, identifying constraints, and supporting proactive decision-making in structural management. By incorporating various perspectives and enabling users to interact with detailed visualizations, the model enhances understanding and maintenance practices. This approach advances defect modeling and digitization, supporting automation in defect detection while significantly contributing to the long-term safety and sustainability of bridges. In order to obtain non-destructive images and films of the morphology of the sandstone’s internal structure at the bridge pier in addition to the stone’s grain texture and surface characteristics, this research applied X-ray computed tomography approach (CT scan) and XRF as NDT to the analysis of sandstone.

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Publication Details

Journal
Buildings
Published
2025-02-06
DOI
https://doi.org/10.3390/buildings15030501
Citations
2
Primary Topic
Infrastructure Maintenance and Monitoring
Type
article
Field-Weighted Citation Impact
1.91
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article

4D Digital Integration for Nanomaterial-Based Monitoring and Treatment of Bridge Piers Defects

Mabrouk Touahmia, Ghazy Abdullah Albaqawy, Abderrahmane Ouazir, Mustapha Boukendakdji et al.
2 citations
Buildings
Infrastructure Maintenance and Monitoring
1.91
article

4D Digital Integration for Nanomaterial-Based Monitoring and Treatment of Bridge Piers Defects

Mabrouk Touahmia, Ghazy Abdullah Albaqawy, Abderrahmane Ouazir, Mustapha Boukendakdji, Mohamed Saleh Sedek, Ahmed Sallam, Abbas Ali Mansour
article en
2 citations

Abstract

This study presents an innovative 4D digital model that integrates Bridge Information Modeling (BrIM) with several types of data to defect detection in complex bridge structures. The model promotes precise data preparation, navigation, visualization, integration, and monitoring, enabling the identification of defects, like material deterioration, condition changes, and structural clashes in components like trusses. Bridge model provides time-based access to maps, allowing users to explore changes over time and predict future conditions. The integration of time dimension into the 4D model provides dynamic tools for exploring changes over time, allowing for analysis and maintenance planning. Through the use of advanced 4D simulation technology, the study’s effectiveness is in visualizing workflows, identifying constraints, and supporting proactive decision-making in structural management. By incorporating various perspectives and enabling users to interact with detailed visualizations, the model enhances understanding and maintenance practices. This approach advances defect modeling and digitization, supporting automation in defect detection while significantly contributing to the long-term safety and sustainability of bridges. In order to obtain non-destructive images and films of the morphology of the sandstone’s internal structure at the bridge pier in addition to the stone’s grain texture and surface characteristics, this research applied X-ray computed tomography approach (CT scan) and XRF as NDT to the analysis of sandstone.

BuildingsVol. 15(3)
South Valley University (EG), University of Ha'il (SA), Aswan University (EG)
Openalex Percentile: Top 18%
Infrastructure Maintenance and Monitoring
1.91
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