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    Rapid Identification and Taxonomical Classification of Structural Seismic Attributes in a Regionwide Commercial Building Stock

    Source: Journal of Performance of Constructed Facilities:;2017:;Volume ( 031 ):;issue: 001
    Author:
    Kevin Q. Walsh
    ,
    Patrick A. Cummuskey
    ,
    Reza Jafarzadeh
    ,
    Jason M. Ingham
    DOI: 10.1061/(ASCE)CF.1943-5509.0000927
    Publisher: American Society of Civil Engineers
    Abstract: As territorial authorities, government agencies, and other large-asset owners were responding to regulatory and market forces in the wake of the 2010–2011 Canterbury, New Zealand, earthquakes by assessing and planning retrofits for buildings determined to be particularly vulnerable to earthquakes, an opportunity existed to identify and taxonomically classify structural seismic attributes in the largest regional commercial building stock in New Zealand. To that end, the Auckland Council proactively sought to assess thousands of commercial and industrial buildings across the Auckland region. As part of the Auckland Council program, a targeted sample out of a total of approximately 19,885 commercial buildings in the Auckland region was assessed with varying amounts of typological data recorded including lateral load resisting system type, number of stories, and time period of construction. Engineers, risk modelers, building regulators, and civil defense officials in other cities around the world can consider the Auckland Council program as a case study for how survey data may be collected, classified, and extrapolated to account for typological information not yet recorded as well as selection biases, and how relatively precise yet rapid assessments may be carried out for especially vulnerable building construction types and components.
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      Rapid Identification and Taxonomical Classification of Structural Seismic Attributes in a Regionwide Commercial Building Stock

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4244181
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    contributor authorKevin Q. Walsh
    contributor authorPatrick A. Cummuskey
    contributor authorReza Jafarzadeh
    contributor authorJason M. Ingham
    date accessioned2017-12-30T12:59:10Z
    date available2017-12-30T12:59:10Z
    date issued2017
    identifier other%28ASCE%29CF.1943-5509.0000927.pdf
    identifier urihttp://138.201.223.254:8080/yetl1/handle/yetl/4244181
    description abstractAs territorial authorities, government agencies, and other large-asset owners were responding to regulatory and market forces in the wake of the 2010–2011 Canterbury, New Zealand, earthquakes by assessing and planning retrofits for buildings determined to be particularly vulnerable to earthquakes, an opportunity existed to identify and taxonomically classify structural seismic attributes in the largest regional commercial building stock in New Zealand. To that end, the Auckland Council proactively sought to assess thousands of commercial and industrial buildings across the Auckland region. As part of the Auckland Council program, a targeted sample out of a total of approximately 19,885 commercial buildings in the Auckland region was assessed with varying amounts of typological data recorded including lateral load resisting system type, number of stories, and time period of construction. Engineers, risk modelers, building regulators, and civil defense officials in other cities around the world can consider the Auckland Council program as a case study for how survey data may be collected, classified, and extrapolated to account for typological information not yet recorded as well as selection biases, and how relatively precise yet rapid assessments may be carried out for especially vulnerable building construction types and components.
    publisherAmerican Society of Civil Engineers
    titleRapid Identification and Taxonomical Classification of Structural Seismic Attributes in a Regionwide Commercial Building Stock
    typeJournal Paper
    journal volume31
    journal issue1
    journal titleJournal of Performance of Constructed Facilities
    identifier doi10.1061/(ASCE)CF.1943-5509.0000927
    page04016067
    treeJournal of Performance of Constructed Facilities:;2017:;Volume ( 031 ):;issue: 001
    contenttypeFulltext
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