Technical Papers
Jul 13, 2022

Creation of a Mock-up Bridge Digital Twin by Fusing Intelligent Transportation Systems (ITS) Data into Bridge Information Model (BrIM)

Publication: Journal of Construction Engineering and Management
Volume 148, Issue 9

Abstract

Passage of overweighted commercial vehicles is one of the significant causes of damage to the pavement and structural components of bridges. Weigh-in-motion (WIM) systems can currently detect real-time traffic data; however, these data are stored in standalone databases. Building information modeling (BIM) has transformed the construction industry by injecting “information” into the building model and integrating different databases. BIM capabilities for bilateral exchange of data led to the inception of digital twin. This research investigates the feasibility of developing a digital twin of a mock-up bridge by integrating WIM data into a bridge information model (BrIM). The system was validated by first creating a mock-up bridge with affixed weight sensors attached to microcomputers and then developing a BrIM model and passing scaled vehicles over in real time with varying weight capacities. This study showed the feasibility of creating digital twins, ultimately enabling future research.

Get full access to this article

View all available purchase options and get full access to this article.

Data Availability Statement

Some or all data, models, or codes that support the findings of this study are available from the corresponding author upon reasonable request.

References

Adibfar, A. 2020. “Bridge digital twins: Fusion of intelligent transportation systems (ITS) sensor data and bridge information modeling (BrIM) for interoperability.” Doctoral dissertation, M. E. Rinker Sr School of Construction Management, Dept. of Design, Construction, and Planning, Univ. of Florida.
Adibfar, A., and A. Costin. 2019a. “Next generation of transportation infrastructure management: Fusion of intelligent transportation systems (ITS) and bridge information modeling (BrIM).” In Advances in informatics and computing in civil and construction engineering, 43–50. Cham, Switzerland: Springer.
Adibfar, A., and A. Costin. 2019b. “Evaluation of IFC for the augmentation of intelligent transportation systems (ITS) into bridge information models (BrIM).” In Proc., ASCE Int. Conf. on Computing in Civil Engineering. Reston, VA: ASCE.
Adibfar, A., and A. Costin. 2021a. “Integrated management of bridge infrastructure through bridge digital twins: A preliminary case study.” In Proc., ASCE Int. Conf. on Computing in Civil Engineering 2021. Reston, VA: ASCE.
Adibfar, A., and A. Costin. 2021b. “Review of data serialization challenges and validation methods for improving interoperability.” In Proc., ASCE Int. Conf. on Computing in Civil Engineering 2021. Reston, VA: ASCE.
Adibfar, A., S. Gulhare, S. Srinivasan, and A. Costin. 2022. Analysis and modeling of changes in online shopping behavior due to COVID-19 pandemic: A Florida case study. Amsterdam, Netherlands: Elsevier.
Akinci, N., J. Liu, and M. Bowman. 2013. “Spring analogy to predict the 3-D live load response of slab-on-girder bridges.” Eng. Struct. 56 (6): 1049–1057. https://doi.org/10.1016/j.engstruct.2013.06.025.
Aroch, R., M. Sokol, and M. Venglar. 2016. “Structural health monitoring of major Danube bridges in Bratislava.” Procedia Eng. 156 (Aug): 24–31. https://doi.org/10.1016/j.proeng.2016.08.263.
ASCE. 2017. “Infrastructure report card.” Accessed July 19, 2018. https://www.infrastructurereportcard.org.
ASCE. 2021. “Infrastructure report card.” Accessed April 1, 2021. https://www.infrastructurereportcard.org.
Badrinath, A., Y. Chang, E. Lin, S. Hsien, and B. Zhao. 2016. “A preliminary study on BIM enabled design warning analysis in T3A terminal of Chongqing Jiangbei international airport.” In Proc., ICCCBE2016-16th Int. Conf. of Computing in Civil and Building Engineering (ICCCBE). Reston, VA: ASCE.
Catbas, F., and M. Malekzadeh. 2016. “A machine learning-based algorithm for processing massive data collected from the mechanical components of movable bridges.” Autom. Constr. 72 (3): 269–278. https://doi.org/10.1016/j.autcon.2016.02.008.
Catbas, F. N., M. Susoy, and D. M. Frangopol. 2008. “Structural health monitoring and reliability estimation: Long span truss bridge application with environmental monitoring data.” Eng. Struct. 30 (9): 2347–2359. https://doi.org/10.1016/j.engstruct.2008.01.013.
Chen, Y. 1996. “Modeling and analysis methods of bridges and their effects on seismic responses: II-implementation.” Comput. Struct. 59 (1): 99–114. https://doi.org/10.1016/0045-7949(95)00226-X.
Costin, A. 2016. “A new methodology for interoperability of heterogeneous bridge information models.” Ph.D. Dissertation, School of Civil & Environmental Engineering, Georgia Institute of Technology.
Costin, A., A. Adibfar, H. Hu, and S. Chen. 2018. “Building information modeling (BIM) for transportation infrastructure—Literature review, applications, challenges, and recommendations.” Autom. Constr. 94 (3): 257–281. https://doi.org/10.1016/j.autcon.2018.07.001.
Costin, A., A. Adibfar, N. Nawari, and C. M. Eastman. 2019. “Preliminary evaluation of the industry foundation classes (IFC) to enable smart city applications.” In Proc., 21st CIB World Building Congress- Constructing smart Cities. Delft, Netherlands: CIB.
Costin, A., and C. Eastman. 2019. “Need for interoperability to enable seamless information exchanges in smart and sustainable urban systems.” J. Comput. Civ. Eng. 33 (3): 04019008. https://doi.org/10.1061/(ASCE)CP.1943-5487.0000824.
Costin, A., and J. Teizer. 2015. “Fusing passive RFID and BIM for increased accuracy in indoor localization.” Visualization Eng. 3 (1): 17. https://doi.org/10.1186/s40327-015-0030-6.
Delgado, J. M., L. J. Butler, N. Gibbons, I. Brilakis, M. Z. Elshafie, and C. Middleton. 2017. “Management of structural monitoring data of bridges using BIM.” J. Bridge Eng. 170 (3): 204–218. https://doi.org/10.1680/jbren.16.00013.
Dygalo, V., A. Keller, and A. Shcherbin. 2020. “Principles of application of virtual and physical simulation technology in the production of digital twin of active vehicle safety systems.” Transp. Res. Procedia 50 (10): 121–129. https://doi.org/10.1016/j.trpro.2020.10.015.
Elnabwy, M., M. Kaloop, and E. Elbeltagi. 2013. “Talkha steel highway bridge monitoring and movement identification using RTK-GPS technique.” Measurement 46 (9): 4282–4292. https://doi.org/10.1016/j.measurement.2013.08.014.
FHWA. 2018. “Truck size and weight research pooled fund project TPF-5(283): The influence of vehicular live loads on bridge performance.” Accessed October 27, 2019. https://highways.dot.gov/bridges-and-structure/long-term-bridge-performance/truck-size-and-weight-research.
Fortino, S., A. Genoese, A. Genoese, L. Nunes, and P. Palma. 2013. “Numerical modeling of the hygro-thermal response of timber bridges during their service life: A monitoring case-study.” Constr. Build. Mater. 47 (6): 1225–1234. https://doi.org/10.1016/j.conbuildmat.2013.06.009.
Hofmann, W., and F. Branding. 2019. “Implementation of an IoT and cloud-based digital twin for real-time decision support in port operations.” IFAC PapersOnLine 52 (13): 2104–2109. https://doi.org/10.1016/j.ifacol.2019.11.516.
Hüthwohl, P., R. Lu, and I. Brilakis. 2016. “Challenges of bridge maintenance inspection.” In Proc., 16th Int. Conf. on Computing in Civil and Building Engineering (ICCCBE2016), edited by N. Yabuki and K. Makanae, 51–58. Osaka, Japan: ICCCBE2016 Organizing Committee.
Jeong, S., J. Byun, D. Kimb, H. Sohn, I. H. Bae, and K. H. Law. 2015. “A data management infrastructure for bridge monitoring.” In Proc., SPIE 9435, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2015, 94350P. Washington, DC: SPIE.
Jeong, S., Y. Zhang, S. O’Connor, J. P. Lynch, H. Sohn, and K. H. Law. 2016. “A NoSQL data management infrastructure for bridge monitoring.” Smart Struct. Syst. 17 (4): 669–690. https://doi.org/10.12989/sss.2016.17.4.669.
Lee, H., M. Lee, I. Lee, and S. Nam. 2017. “A study on the development of 3d parametric model for reinforced concrete bridge piers.” In Proc., Int. Conf. of Computing in Civil and Building Engineering (ICCCBE), 102–105. Reston, VA: ASCE.
Li, J., and H. Hao. 2016. “Health monitoring of joint conditions in steel truss bridges with relative displacement sensors.” Measurement 88 (2): 360–371. https://doi.org/10.1016/j.measurement.2015.12.009.
Liu, K., and N. El-Gohary. 2017. “Ontology-based semi-supervised conditional random fields for automated information extraction from bridge inspection reports.” Autom. Constr. 81 (Feb): 313–327. https://doi.org/10.1016/j.autcon.2017.02.003.
Maeda, K., S. Takahashi, T. Ogawa, and M. Haseyama. 2017. “Distress classification of class imbalanced data for maintenance inspection of road structures in expressway.” In Proc., Int. Conf. of Computing in Civil and Building Engineering (ICCCBE). Reston, VA: ASCE.
Marzouk, M., and M. Hisham. 2011. “Bridge information modeling in sustainable bridge management.” In Proc., Int. Conf. on Sustainable Design and Construction (ICSDC), 457–466. Reston, VA: ASCE.
McGuire, B., R. Atadero, C. Clevenger, and M. Ozbek. 2016. “Bridge information modeling for inspection and evaluation.” J. Bridge Eng. 21 (4): 04015076. https://doi.org/10.1061/(ASCE)BE.1943-5592.0000850.
Metni, N., and T. Hamel. 2007. “A UAV for bridge inspection: Visual servoing control law with orientation limits.” Autom. Constr. 17 (Dec): 3–10. https://doi.org/10.1016/j.autcon.2006.12.010.
Motamedi, A., N. Yabuki, and T. Fukuda. 2017. “Extending BIM to include defects and degradations of buildings and infrastructure facilities.” In Proc., Int. Conf. of Civil and Building Engineering Informatics (ICCBEI), 110–113. Reston, VA: ASCE.
Oh, J., G. Jang, S. Oh, J. H. Lee, B. Yi, Y. S. Moon, J. S. Lee, and Y. Choi. 2009. “Bridge inspection robot system with machine vision.” Autom. Constr. 18 (Jan): 929–941. https://doi.org/10.1016/j.autcon.2009.04.003.
Okasha, N., and D. Frangopol. 2011. “Computational platform for the integrated life-cycle management of highway bridges.” Eng. Struct. 33 (Mar): 2145–2153. https://doi.org/10.1016/j.engstruct.2011.03.005.
Prendergast, L. J., and K. Gavin. 2014. “A review of bridge scour monitoring techniques.” J. Rock Mech. Geotech. Eng. 6 (2): 138–149. https://doi.org/10.1016/j.jrmge.2014.01.007.
Sekiya, H., O. Maruyama, and C. Miki. 2017. “Visualization system for bridge deformations under live load based on multipoint simultaneous measurements of displacement and rotational response using MEMS sensors.” Eng. Struct. 146 (Sep): 43–53. https://doi.org/10.1016/j.engstruct.2017.05.036.
Sofia, H., E. Anas, and O. Faiz. 2020. “Mobile mapping, machine learning and digital twin for road infrastructure monitoring and maintenance: Case study of Mohammed VI Bridge in Morocco.” In Proc., 2020 IEEE Int. Conf. of Moroccan Geomatics (Morgeo). New York: IEEE.
Teng, S., M. Toud, W. Leong, B. How, H. Lam, and V. Masa. 2021. “Recent advances on industrial data-driven energy savings: Digital twins and infrastructures.” Renewable Sustainable Energy Rev. 135 (Apr): 110208. https://doi.org/10.1016/j.rser.2020.110208.
Tochaei, E., Z. Fang, T. Taylor, S. Babanajad, and F. Ansari. 2021. “Structural monitoring and remaining fatigue life estimation of typical welded crack details in the Manhattan bridge.” Eng. Struct. 231 (11): 111760. https://doi.org/10.1016/j.engstruct.2020.111760.
Zhiming, B., T. Jianhang, W. Mengyao, W. Siqi, and H. Yuxin. 2019. “In depth: Overloaded and overturned—Inside the deadly Wuxi bridge collapse.” Accessed November 1, 2019. https://www.caixinglobal.com/2019-11-01/in-depth-overloaded-and-overturned-inside-the-deadly-wuxi-bridge-collapse-101478011.html.
Zou, Y., A. Kiviniemi, and S. Jones. 2017. “A review of risk management through BIM and BIM-related technologies.” Saf. Sci. 97 (Dec): 88–98. https://doi.org/10.1016/j.ssci.2015.12.027.

Information & Authors

Information

Published In

Go to Journal of Construction Engineering and Management
Journal of Construction Engineering and Management
Volume 148Issue 9September 2022

History

Received: Sep 2, 2021
Accepted: Apr 11, 2022
Published online: Jul 13, 2022
Published in print: Sep 1, 2022
Discussion open until: Dec 13, 2022

Permissions

Request permissions for this article.

Authors

Affiliations

M.E. Rinker Sr. School of Construction Management, Univ. of Florida, 323 Rinker Hall, Gainesville, FL 32603 (corresponding author). ORCID: https://orcid.org/0000-0002-6952-3091. Email: [email protected]
Aaron M. Costin, Ph.D., A.M.ASCE [email protected]
Assistant Professor, M.E. Rinker Sr. School of Construction Management, Univ. of Florida, 323 Rinker Hall, Gainesville, FL 32603. Email: [email protected]

Metrics & Citations

Metrics

Citations

Download citation

If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.

Cited by

  • Semiautomated Railway Line Information Modeling Based on Asset Management Data, Journal of Construction Engineering and Management, 10.1061/JCEMD4.COENG-15011, 150, 10, (2024).
  • Digital Twin for Bridges and Structures: Practical Applications and Challenges, Digital Twins in Construction and the Built Environment, 10.1061/9780784485606.ch11, (251-268), (2024).
  • Digital Twin and Industry 4.0 Enablers in Building and Construction: A Survey, Buildings, 10.3390/buildings12112004, 12, 11, (2004), (2022).
  • Digital twins and innovation management: a literature review, framework, challenge, and future direction, Technology Analysis & Strategic Management, 10.1080/09537325.2022.2131518, (1-14), (2022).

View Options

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Media

Figures

Other

Tables

Share

Share

Copy the content Link

Share with email

Email a colleague

Share