Digital twin aided vulnerability assessment and risk-based maintenance planning of bridge infrastructures exposed to extreme conditions

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Digital twin aided vulnerability assessment and risk-based maintenance planning of bridge infrastructures exposed to extreme conditions. / Kaewunruen, Sakdirat; Sresakoolchai, Jessada; Ma, Wentao; Phil-Ebosie, Olisa.

In: Sustainability (Switzerland), Vol. 13, No. 4, 2051, 14.02.2021.

Research output: Contribution to journalArticlepeer-review

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@article{913c2cd64fff468090a1c60aa18902a9,
title = "Digital twin aided vulnerability assessment and risk-based maintenance planning of bridge infrastructures exposed to extreme conditions",
abstract = "Over the past centuries, millions of bridge infrastructures have been constructed globally. Many of those bridges are ageing and exhibit significant potential risks. Frequent risk-based inspection and maintenance management of highway bridges is particularly essential for public safety. At present, most bridges rely on manual inspection methods for management. The efficiency is extremely low, causing the risk of bridge deterioration and defects to increase day by day, reducing the load-bearing capacity of bridges, and restricting the normal and safe use of them. At present, the applications of digital twins in the construction industry have gained significant momentum and the industry has gradually entered the information age. In order to obtain and share relevant information, engineers and decision makers have adopted digital twins over the entire life cycle of a project, but their applications are still limited to data sharing and visualization. This study has further demonstrated the unprecedented applications of digital twins to sustainability and vulnerability assessments, which can enable the next generation risk-based inspection and maintenance framework. This study adopts the data obtained from a constructor of Zhongcheng Village Bridge in Zhejiang Province, China as a case study. The applications of digital twins to bridge model establishment, information collection and sharing, data processing, inspection and maintenance planning have been highlighted. Then, the integration of “digital twins (or Building Information Modelling, BIM) + bridge risk inspection model” has been established, which will become a more effective information platform for all stakeholders to mitigate risks and uncertainties of exposure to extreme weather conditions over the entire life cycle.",
keywords = "BIM, Bridge, Extreme condition, Inspection, Life cycle, Risk-based maintenance, Sustainable development, Vulnerability",
author = "Sakdirat Kaewunruen and Jessada Sresakoolchai and Wentao Ma and Olisa Phil-Ebosie",
note = "Funding Information: This research was funded by Japan Society for the Promotion of Sciences for his Invitation Research Fellowship (Long-term), Grant No. JSPS-L15701 and the European Commission for the H2020-RISE Project No. 691135 ?RISEN: Rail Infrastructure Systems Engineering Network?. The APC is sponsored by MDPI?s invited paper program. The corresponding author is sincerely grateful to the Australian Academy of Science and the Japan Society for the Promotion of Sciences for his JSPS Invitation Research Fellowship (Long-term), Grant No. JSPS-L15701 at the Railway Technical Research Institute and the University of Tokyo, Japan. The authors are also wishing to thank to the European Commission for the financial sponsorship of the H2020-RISE Project No. 691135 ?RISEN: Rail Infrastructure Systems Engineering Network?, which enables a global research network that tackles the grand challenge of railway infrastructure resilience and advanced sensing in extreme environments (www.risen2rail.eu). Publisher Copyright: {\textcopyright} 2021 by the authors.",
year = "2021",
month = feb,
day = "14",
doi = "10.3390/su13042051",
language = "English",
volume = "13",
journal = "Sustainability",
issn = "2071-1050",
publisher = "MDPI",
number = "4",

}

RIS

TY - JOUR

T1 - Digital twin aided vulnerability assessment and risk-based maintenance planning of bridge infrastructures exposed to extreme conditions

AU - Kaewunruen, Sakdirat

AU - Sresakoolchai, Jessada

AU - Ma, Wentao

AU - Phil-Ebosie, Olisa

N1 - Funding Information: This research was funded by Japan Society for the Promotion of Sciences for his Invitation Research Fellowship (Long-term), Grant No. JSPS-L15701 and the European Commission for the H2020-RISE Project No. 691135 ?RISEN: Rail Infrastructure Systems Engineering Network?. The APC is sponsored by MDPI?s invited paper program. The corresponding author is sincerely grateful to the Australian Academy of Science and the Japan Society for the Promotion of Sciences for his JSPS Invitation Research Fellowship (Long-term), Grant No. JSPS-L15701 at the Railway Technical Research Institute and the University of Tokyo, Japan. The authors are also wishing to thank to the European Commission for the financial sponsorship of the H2020-RISE Project No. 691135 ?RISEN: Rail Infrastructure Systems Engineering Network?, which enables a global research network that tackles the grand challenge of railway infrastructure resilience and advanced sensing in extreme environments (www.risen2rail.eu). Publisher Copyright: © 2021 by the authors.

PY - 2021/2/14

Y1 - 2021/2/14

N2 - Over the past centuries, millions of bridge infrastructures have been constructed globally. Many of those bridges are ageing and exhibit significant potential risks. Frequent risk-based inspection and maintenance management of highway bridges is particularly essential for public safety. At present, most bridges rely on manual inspection methods for management. The efficiency is extremely low, causing the risk of bridge deterioration and defects to increase day by day, reducing the load-bearing capacity of bridges, and restricting the normal and safe use of them. At present, the applications of digital twins in the construction industry have gained significant momentum and the industry has gradually entered the information age. In order to obtain and share relevant information, engineers and decision makers have adopted digital twins over the entire life cycle of a project, but their applications are still limited to data sharing and visualization. This study has further demonstrated the unprecedented applications of digital twins to sustainability and vulnerability assessments, which can enable the next generation risk-based inspection and maintenance framework. This study adopts the data obtained from a constructor of Zhongcheng Village Bridge in Zhejiang Province, China as a case study. The applications of digital twins to bridge model establishment, information collection and sharing, data processing, inspection and maintenance planning have been highlighted. Then, the integration of “digital twins (or Building Information Modelling, BIM) + bridge risk inspection model” has been established, which will become a more effective information platform for all stakeholders to mitigate risks and uncertainties of exposure to extreme weather conditions over the entire life cycle.

AB - Over the past centuries, millions of bridge infrastructures have been constructed globally. Many of those bridges are ageing and exhibit significant potential risks. Frequent risk-based inspection and maintenance management of highway bridges is particularly essential for public safety. At present, most bridges rely on manual inspection methods for management. The efficiency is extremely low, causing the risk of bridge deterioration and defects to increase day by day, reducing the load-bearing capacity of bridges, and restricting the normal and safe use of them. At present, the applications of digital twins in the construction industry have gained significant momentum and the industry has gradually entered the information age. In order to obtain and share relevant information, engineers and decision makers have adopted digital twins over the entire life cycle of a project, but their applications are still limited to data sharing and visualization. This study has further demonstrated the unprecedented applications of digital twins to sustainability and vulnerability assessments, which can enable the next generation risk-based inspection and maintenance framework. This study adopts the data obtained from a constructor of Zhongcheng Village Bridge in Zhejiang Province, China as a case study. The applications of digital twins to bridge model establishment, information collection and sharing, data processing, inspection and maintenance planning have been highlighted. Then, the integration of “digital twins (or Building Information Modelling, BIM) + bridge risk inspection model” has been established, which will become a more effective information platform for all stakeholders to mitigate risks and uncertainties of exposure to extreme weather conditions over the entire life cycle.

KW - BIM

KW - Bridge

KW - Extreme condition

KW - Inspection

KW - Life cycle

KW - Risk-based maintenance

KW - Sustainable development

KW - Vulnerability

UR - http://www.scopus.com/inward/record.url?scp=85101241361&partnerID=8YFLogxK

U2 - 10.3390/su13042051

DO - 10.3390/su13042051

M3 - Article

VL - 13

JO - Sustainability

JF - Sustainability

SN - 2071-1050

IS - 4

M1 - 2051

ER -