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    Multiaspect Similarity Evaluation of BIM-Based Standard Dwelling Units for Residential Design

    Source: Journal of Computing in Civil Engineering:;2018:;Volume ( 032 ):;issue: 005
    Author:
    He Tianfeng;Zhang Jianping;Lin Jiarui;Li Yungui
    DOI: 10.1061/(ASCE)CP.1943-5487.0000774
    Publisher: American Society of Civil Engineers
    Abstract: The standard dwelling unit (SDU) has been adopted to standardize dwelling units and to reuse them in residential design, especially in the floor-plan design of multifloor buildings. However, conventional attribute-based search methods fail to represent important features, such as topology and shape, making it difficult to fully utilize the previously obtained information. Because building information models (BIMs) are replacing drawings and documents in storing and managing SDUs, this paper proposes a multiaspect similarity evaluation method to provide a more comprehensive way to search SDUs in residential design. The proposed approach introduced six similarities and their corresponding evaluation methods from the aspects of attribute, topology, and shape. Furthermore, a combined similarity was proposed to combine different similarities to reflect designers’ search intentions. Finally, a database with 17 SDUs and a prototype design tool were developed and tested in two projects. The application showed that the proposed method is capable of evaluating the similarity of SDUs in a more comprehensive manner and increasing the efficiency and quality of the search for SDU alternatives in the residential design process.
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      Multiaspect Similarity Evaluation of BIM-Based Standard Dwelling Units for Residential Design

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    https://yetl.yabesh.ir/yetl1/handle/yetl/4248635
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    contributor authorHe Tianfeng;Zhang Jianping;Lin Jiarui;Li Yungui
    date accessioned2019-02-26T07:40:26Z
    date available2019-02-26T07:40:26Z
    date issued2018
    identifier other%28ASCE%29CP.1943-5487.0000774.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4248635
    description abstractThe standard dwelling unit (SDU) has been adopted to standardize dwelling units and to reuse them in residential design, especially in the floor-plan design of multifloor buildings. However, conventional attribute-based search methods fail to represent important features, such as topology and shape, making it difficult to fully utilize the previously obtained information. Because building information models (BIMs) are replacing drawings and documents in storing and managing SDUs, this paper proposes a multiaspect similarity evaluation method to provide a more comprehensive way to search SDUs in residential design. The proposed approach introduced six similarities and their corresponding evaluation methods from the aspects of attribute, topology, and shape. Furthermore, a combined similarity was proposed to combine different similarities to reflect designers’ search intentions. Finally, a database with 17 SDUs and a prototype design tool were developed and tested in two projects. The application showed that the proposed method is capable of evaluating the similarity of SDUs in a more comprehensive manner and increasing the efficiency and quality of the search for SDU alternatives in the residential design process.
    publisherAmerican Society of Civil Engineers
    titleMultiaspect Similarity Evaluation of BIM-Based Standard Dwelling Units for Residential Design
    typeJournal Paper
    journal volume32
    journal issue5
    journal titleJournal of Computing in Civil Engineering
    identifier doi10.1061/(ASCE)CP.1943-5487.0000774
    page4018032
    treeJournal of Computing in Civil Engineering:;2018:;Volume ( 032 ):;issue: 005
    contenttypeFulltext
    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian
     
    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian