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    Real-Time Risk Assessment of Tunneling-Induced Building Damage Considering Polymorphic Uncertainty

    Source: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering:;2021:;Volume ( 008 ):;issue: 001::page 04021069
    Author:
    Ba Trung Cao
    ,
    Markus Obel
    ,
    Steffen Freitag
    ,
    Lukas Heußner
    ,
    Günther Meschke
    ,
    Peter Mark
    DOI: 10.1061/AJRUA6.0001192
    Publisher: ASCE
    Abstract: The risk assessment of tunneling-induced damage in buildings is a challenging task in geotechnical and structural engineering. It is important to consider the soil–structure interaction during the tunnel construction process. In this paper, finite-element (FE) simulation models of mechanized tunneling processes are combined with FE models of buildings to predict tunneling-induced damage. The soil–structure interaction is taken into account by considering the building stiffness in the tunneling process simulation model and by applying the computed foundation settlements as boundary conditions of the building model. The building damage risk is assessed by means of strains in the structural members and a corresponding category of damage is determined. Uncertainties of the geotechnical parameters and the structural parameters are quantified as random variables and intervals in the framework of polymorphic uncertainty modeling. For real-time predictions, the FE simulation models are approximated by artificial neural networks. This makes it possible to predict the structural damage risk according to scenarios of the operational tunneling process parameters in order to assist machine drivers during tunnel construction.
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      Real-Time Risk Assessment of Tunneling-Induced Building Damage Considering Polymorphic Uncertainty

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    • ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering

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    contributor authorBa Trung Cao
    contributor authorMarkus Obel
    contributor authorSteffen Freitag
    contributor authorLukas Heußner
    contributor authorGünther Meschke
    contributor authorPeter Mark
    date accessioned2022-05-07T20:39:09Z
    date available2022-05-07T20:39:09Z
    date issued2021-10-19
    identifier otherAJRUA6.0001192.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4282712
    description abstractThe risk assessment of tunneling-induced damage in buildings is a challenging task in geotechnical and structural engineering. It is important to consider the soil–structure interaction during the tunnel construction process. In this paper, finite-element (FE) simulation models of mechanized tunneling processes are combined with FE models of buildings to predict tunneling-induced damage. The soil–structure interaction is taken into account by considering the building stiffness in the tunneling process simulation model and by applying the computed foundation settlements as boundary conditions of the building model. The building damage risk is assessed by means of strains in the structural members and a corresponding category of damage is determined. Uncertainties of the geotechnical parameters and the structural parameters are quantified as random variables and intervals in the framework of polymorphic uncertainty modeling. For real-time predictions, the FE simulation models are approximated by artificial neural networks. This makes it possible to predict the structural damage risk according to scenarios of the operational tunneling process parameters in order to assist machine drivers during tunnel construction.
    publisherASCE
    titleReal-Time Risk Assessment of Tunneling-Induced Building Damage Considering Polymorphic Uncertainty
    typeJournal Paper
    journal volume8
    journal issue1
    journal titleASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
    identifier doi10.1061/AJRUA6.0001192
    journal fristpage04021069
    journal lastpage04021069-18
    page18
    treeASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering:;2021:;Volume ( 008 ):;issue: 001
    contenttypeFulltext
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