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Book Chapter

A BIM-Based Approach to the Management of Historic Bridges

  • Carlo Biagini
  • Alberto Aglietti
  • Andrea Bongini

Building Information Modelling applied to civil infrastructure has opened up interesting scenarios for integrated management of existing infrastructural works. In the last few years Bridge Management System (BMS) have been increasingly used by infrastructure owners, based on different control systems: from stochastic methods, which make it possible to define a condition ratio (CR) starting from periodic inspections of bridges, to sensors for structural monitoring, which can originate a flow of information exchange between real artifacts and the digital model capable of activating effective reactive or planned responses in the operation and maintenance phase of the asset. The paper intends to outline a BIM-oriented process workflow, which from the creation of parametric objects for infrastructural works using Scan-to-BIM acquisition techniques and procedures, arrives at the implementation of information bridge models to manage both static data from scheduled inspections of technicians of defects and their severity according to specific guidelines, and dynamic data from incoming and outgoing sensors placed in the physical asset for real time monitoring towards analysis, supervision and control systems of the facilities owner. The defined process workflow will be applied to some case studies, related to bridges of different characteristics, outlining some directions for future developments. In detail the research showcases the tasks undertaken and the outcomes achieved on four selected bridge case studies, which are real and situated within the geographical area of the Tuscany region, Italy. The studied bridges are all still in use and hold historical significance, as they were constructed between two hundred and one hundred years ago

  • Keywords:
  • Bridge Management System; InfraBIM; HBrIM; Digital Twin,
  • Scan-to-BIM,
  • SHM,
  • IFC,
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Carlo Biagini

University of Florence, Italy - ORCID: 0000-0002-0737-2187

Alberto Aglietti

University of Florence, Italy - ORCID: 0009-0008-3719-2874

Andrea Bongini

University of Florence, Italy - ORCID: 0000-0001-8832-2319

  1. Agrawal, A., Gans, J., & Goldfarb, A. (2018). Prediction machines: The simple economics of artificial intelligence. Harvard Business Review Press.
  2. Agrawal, A., Gans, J., & Goldfarb, A. (2022). Power and prediction: The disruptive economics of artificial intelligence. Harvard Business Review Press.
  3. Barazzetti, L., Banfi, F., Brumana, R., Previtali, M., & Roncoroni, F. (2016). BIM FROM LASER SCANS… NOT JUST FOR BUILDINGS: NURBS-BASED PARAMETRIC MODELING OF A MEDIEVAL BRIDGE. ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences, III–5, 51–56. DOI: 10.5194/isprsannals-III-5-51-2016
  4. Boardman, C., Bryan, P., McDougall, L., Reuter, T., Payne, E., Moitinho, V., Rodgers, T., Honkova, J., O’Connor, L., Blockley, C., Andrews, D., Bedford, J., Sawdon, S., Hook, L., Green, R., Price, K., Klÿn, N., & Abbott, M. (2018). 3D Laser Scanning for Heritage. Advice and Guidance on the Use of Laser Scanning in Archaeology and Architecture.
  5. Borin, P., & Cavazzini, F. (2019). CONDITION ASSESSMENT OF RC BRIDGES. INTEGRATING MACHINE LEARNING, PHOTOGRAMMETRY AND BIM. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLII-2/W15, 201–208. DOI: 10.5194/isprs-archives-XLII-2-W15-201-2019
  6. Croce, V., Caroti, G., Piemonte, A., De Luca, L., & Véron, P. (2023). H-BIM and Artificial Intelligence: Classification of Architectural Heritage for Semi-Automatic Scan-to-BIM Reconstruction. Sensors, 23(5), 2497. DOI: 10.3390/s23052497
  7. de Freitas Bello, V. S., Popescu, C., Blanksvärd, T., & Täljsten, B. (2021). Bridge management systems: Overview and framework for smart management. 1014–1022. DOI: 10.2749/ghent.2021.1014
  8. Ioli, F., Pinto, A., & Pinto, L. (2022). UAV PHOTOGRAMMETRY FOR METRIC EVALUATION OF CONCRETE BRIDGE CRACKS. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLIII-B2-2022, 1025–1032. DOI: 10.5194/isprs-archives-XLIII-B2-2022-1025-2022
  9. Jáuregui, D., Tian, Y., & Jiang, R. (2006). Photogrammetry Applications in Routine Bridge Inspection and Historic Bridge Documentation. Transportation Research Record: Journal of the Transportation Research Board, 1958, 24–32. DOI: 10.1177/0361198106195800103
  10. Kaewunruen, S., AbdelHadi, M., Kongpuang, M., Pansuk, W., & Remennikov, A. M. (2022). Digital Twins for Managing Railway Bridge Maintenance, Resilience, and Climate Change Adaptation. Sensors, 23(1), 252. DOI: 10.3390/s23010252
  11. León-Robles, C., Reinoso-Gordo, J., & González-Quiñones, J. (2019). Heritage Building Information Modeling (H-BIM) Applied to A Stone Bridge. ISPRS International Journal of Geo-Information, 8(3), 121. DOI: 10.3390/ijgi8030121
  12. Li, S., Zhang, Z., Lin, D., Zhang, T., & Han, L. (2023). Development of a BIM-based bridge maintenance system (BMS) for managing defect data. Scientific Reports, 13(1), 846. DOI: 10.1038/s41598-023-27924-6
  13. Malekloo, A., Ozer, E., AlHamaydeh, M., & Girolami, M. (2022). Machine learning and structural health monitoring overview with emerging technology and high-dimensional data source highlights. Structural Health Monitoring, 21(4), 1906–1955. DOI: 10.1177/14759217211036880
  14. Mohammadi, M., Rashidi, M., Mousavi, V., Karami, A., Yu, Y., & Samali, B. (2021). Quality Evaluation of Digital Twins Generated Based on UAV Photogrammetry and TLS: Bridge Case Study. Remote Sensing, 13(17), 3499. DOI: 10.3390/rs13173499
  15. Murphy, M., Mcgovern, E., & Pavía, S. (2011). Historic Building Information Modelling—Adding intelligence to laser and image based surveys of European classical architecture. In International Journal of Photogrammetry and Remote Sensing (Vol. 76). DOI: 10.1016/j.isprsjprs.2012.11.006
  16. Osello, A. (A c. Di). (2019). InfraBIM: Il BIM per le infrastrutture. Gangemi.
  17. Pritchard, D., Sperner, J., Hoepner, S., & Tenschert, R. (2017). Terrestrial laser scanning for heritage conservation:the Cologne Cathedral documentation project. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, IV-2/W2, 213–220. DOI: 10.5194/isprs-annals-IV-2-W2-213-2017
  18. Roggeri, S., Vassena, G., & Tagliabue, L. (2022). SCAN-TO-BIM EFFICIENT APPROACH TO EXTRACT BIM MODELS FROM HIGH PRODUCTIVE INDOOR MOBILE MAPPING SURVEY. Proceedings of International Structural Engineering and Construction, 9. DOI: 10.14455/ISEC.2022.9(1).AAE-16
  19. Saback de Freitas Bello, V., Popescu, C., Blanksvärd, T., & Täljsten, B. (2022). Framework for Bridge Management Systems (BMS) Using Digital Twins. In C. Pellegrino, F. Faleschini, M. A. Zanini, J. C. Matos, J. R. Casas, & A. Strauss (A c. Di), Proceedings of the 1st Conference of the European Association on Quality Control of Bridges and Structures (Vol. 200, pp. 687–694). Springer International Publishing. DOI: 10.1007/978-3-030-91877-4_78
  20. Saback, V., Popescu, C., Blanksvärd, T., & Täljsten, B. (2022). Asset Management of Existing Concrete Bridges Using Digital Twins and BIM: A State-of-the-Art Literature Review. Nordic Concrete Research, 66(1), 91–111. DOI: 10.2478/ncr-2021-0020
  21. Santarsiero, G., Masi, A., Picciano, V., & Digrisolo, A. (2021). The Italian Guidelines on Risk Classification and Management of Bridges: Applications and Remarks on Large Scale Risk Assessments. Infrastructures, 6(8), 111. DOI: 10.3390/infrastructures6080111
  22. Sing, M. C. P., Sophie, Y. Y., Chan, K., Liu, H., & Humphrey, R. (2022). Scan-to-BIM technique in building maintenance projects: Practicing quantity take-off. International Journal of Building Pathology and Adaptation. DOI: 10.1108/IJBPA-06-2022-0097
  23. Stavroulaki, M. E., Riveiro, B., Drosopoulos, G. A., Solla, M., Koutsianitis, P., & Stavroulakis, G. E. (2016). Modelling and strength evaluation of masonry bridges using terrestrial photogrammetry and finite elements. Advances in Engineering Software, 101, 136–148. DOI: 10.1016/j.advengsoft.2015.12.007
  24. Wang, Q., Guo, J., & Kim, M.-K. (2019). An Application Oriented Scan-to-BIM Framework. Remote Sensing, 11(3), 365. DOI: 10.3390/rs11030365
  25. Woodward, R., CULLINGTON, D., DALY, A., VASSIE, P., HAARDT, P., KASHNER, R., ASTUDILLO, R., VELANDO, C., Godart, B., & Cremona, C. (2001). BRIDGE MANAGEMENT IN EUROPE (BRIME)-DELIVERABLE D14-FINAL REPORT.
  26. Zinno, R., Haghshenas, S. S., Guido, G., & VItale, A. (2022). Artificial Intelligence and Structural Health Monitoring of Bridges: A Review of the State-of-the-Art. IEEE Access, 10, 88058–88078. DOI: 10.1109/ACCESS.2022.3199443
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  • Publication Year: 2023
  • Pages: 1105-1116

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  • Publication Year: 2023

Chapter Information

Chapter Title

A BIM-Based Approach to the Management of Historic Bridges

Authors

Carlo Biagini, Alberto Aglietti, Andrea Bongini

DOI

10.36253/979-12-215-0289-3.110

Peer Reviewed

Publication Year

2023

Copyright Information

© 2023 Author(s)

Content License

CC BY-NC 4.0

Metadata License

CC0 1.0

Bibliographic Information

Book Title

CONVR 2023 - Proceedings of the 23rd International Conference on Construction Applications of Virtual Reality

Book Subtitle

Managing the Digital Transformation of Construction Industry

Editors

Pietro Capone, Vito Getuli, Farzad Pour Rahimian, Nashwan Dawood, Alessandro Bruttini, Tommaso Sorbi

Peer Reviewed

Publication Year

2023

Copyright Information

© 2023 Author(s)

Content License

CC BY-NC 4.0

Metadata License

CC0 1.0

Publisher Name

Firenze University Press

DOI

10.36253/979-12-215-0289-3

eISBN (pdf)

979-12-215-0289-3

eISBN (xml)

979-12-215-0257-2

Series Title

Proceedings e report

Series ISSN

2704-601X

Series E-ISSN

2704-5846

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