Development of BrIM-Based Bridge Maintenance System for Existing Bridges

Abstract

Globally, bridges are rapidly aging, and traditional maintenance approaches face significant challenges in terms of efficiency and cost. To overcome these challenges, considerable research has been conducted to introduce enhanced bridge management systems (BMSs) based on bridge information modeling (BrIM) from various perspectives. However, most studies have highlighted the advantages of BrIM, while neglecting the practical issues that potential users may encounter on existing bridges. The primary problem is digitizing existing bridges that have not yet adopted BrIM. The universal applicability of BrIM should be carefully considered from the perspective of national maintenance authorities managing thousands of bridges, because modeling based on commercial software is expected to be time-consuming and costly. Therefore, in this study, information and functional requirements were derived from interviews with stakeholders, including bridge owners, managers, and site inspectors. Based on this understanding, a data-driven modeling approach using basic bridge information was implemented, and an inventory code system was integrated to efficiently manage and utilize the data. Moreover, mapping and deep learning-based vectorization were considered for managing inspection information, and features for bridge assessment, dashboards, and reporting were incorporated to support decision-making. The developed BrIM demonstrated the potential for enhancing maintenance efficiency through a case study. Particularly, significant improvements were observed in mandatory documentation tasks, along with their investigation and analysis, as required by regulations. Additionally, efficient modeling and data management were achieved for the existing bridge.

Framework for assessing bridges construction impact on work zone traffic using BrIM

“…Through proactive planning and improved use of the available data, the study's findings will contribute to the sustainability, preservation, and resilience of bridges. Jeon et al 9 implemented a data-driven modeling approach using basic bridge information and integrated an inventory code system to effectively manage and utilize the data. Additionally, mapping and deep learning-based vectorization were taken into consideration for managing inspection information, and features for bridge assessment, dashboards, and reporting were incorporated to support decision-making.…”

An Integrated Data-Driven System for Digital Bridge Management

“…These collapses have generated the need to establish efficient tools for the maintenance and management of bridges, which has led to the development of several bridge management systems (BMSs), including the preservation, optimization and network information system (PONTIS [7]) in the United States, the Japanese bridge management system (J-BMS [8]), and the BaTMan (Sweden), BAUT (Austria), DANBRO (Denmark [9]), Within this framework, the present paper proposes an integrated data-driven approach for bridge management digitalization at the regional scale, coherent with the multi-level approach for the safety management of existing bridges outlined in the abovementioned guidelines published by the Italian MIT [13,14]. A unified relational database (RDB) is used to derive, through SQL cross-analysis queries, the fundamental data for BIM [18][19][20] design, geographic information system (GIS) [21,22] cataloguing, and calculations through existing algorithms [23,24]. In particular, the information stored in the RDB is automatically made available in GIS and allows the automatic generation of preliminary BIM models, which can be enriched with multi-source data derived from the use of the latest technologies.…”