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    Integrated Information Repository for Risk Assessment of Embankment Dams: Requirements Identification for Evaluating the Risk of Internal Erosion

    Source: Journal of Computing in Civil Engineering:;2016:;Volume ( 030 ):;issue: 003
    Author:
    Nur Sila Gulgec
    ,
    Semiha Ergan
    ,
    Burcu Akinci
    ,
    Christopher J. Kelly
    DOI: 10.1061/(ASCE)CP.1943-5487.0000509
    Publisher: American Society of Civil Engineers
    Abstract: Dams are continuing to age and deteriorate that affect the service life of the dams in the U.S. Risk assessment is required to understand the behavior of dams and to prioritize the remedial actions and maintenance, and yet it is quite challenging to do risk assessment since it requires extensive current and historical data from in situ instrumentation on dams and detailed design, construction, and operation information. Currently, the required data for risk assessment resides in various paper-based and digital documents that hinder the capabilities of risk assessors to gather, analyze, and visualize the data flexibly from various engineering perspectives such as geotechnical, hydrologic, geologic, and structural. As a result, getting a holistic view of a dam’s current condition and its behavior over time becomes a time and resource intensive task. There is a need for an integrated shared knowledge repository for dams to streamline the risk assessment process. The research described in this paper provides requirements for developing such a shared knowledge repository for risk assessment of embankment dams that would support the information needs of various engineering domains and the means and methods for integrated assessment, visualization, and data analytics to understand the risk of internal erosion.
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      Integrated Information Repository for Risk Assessment of Embankment Dams: Requirements Identification for Evaluating the Risk of Internal Erosion

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    http://yetl.yabesh.ir/yetl1/handle/yetl/80816
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    contributor authorNur Sila Gulgec
    contributor authorSemiha Ergan
    contributor authorBurcu Akinci
    contributor authorChristopher J. Kelly
    date accessioned2017-05-08T22:27:01Z
    date available2017-05-08T22:27:01Z
    date copyrightMay 2016
    date issued2016
    identifier other45444180.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/80816
    description abstractDams are continuing to age and deteriorate that affect the service life of the dams in the U.S. Risk assessment is required to understand the behavior of dams and to prioritize the remedial actions and maintenance, and yet it is quite challenging to do risk assessment since it requires extensive current and historical data from in situ instrumentation on dams and detailed design, construction, and operation information. Currently, the required data for risk assessment resides in various paper-based and digital documents that hinder the capabilities of risk assessors to gather, analyze, and visualize the data flexibly from various engineering perspectives such as geotechnical, hydrologic, geologic, and structural. As a result, getting a holistic view of a dam’s current condition and its behavior over time becomes a time and resource intensive task. There is a need for an integrated shared knowledge repository for dams to streamline the risk assessment process. The research described in this paper provides requirements for developing such a shared knowledge repository for risk assessment of embankment dams that would support the information needs of various engineering domains and the means and methods for integrated assessment, visualization, and data analytics to understand the risk of internal erosion.
    publisherAmerican Society of Civil Engineers
    titleIntegrated Information Repository for Risk Assessment of Embankment Dams: Requirements Identification for Evaluating the Risk of Internal Erosion
    typeJournal Paper
    journal volume30
    journal issue3
    journal titleJournal of Computing in Civil Engineering
    identifier doi10.1061/(ASCE)CP.1943-5487.0000509
    treeJournal of Computing in Civil Engineering:;2016:;Volume ( 030 ):;issue: 003
    contenttypeFulltext
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