دانلود مقاله ISI انگلیسی شماره 151599
ترجمه فارسی عنوان مقاله

منطق برای اطمینان از یکپارچگی مبادله داده ها از مدل های اطلاعات ساختمان

عنوان انگلیسی
Logic for ensuring the data exchange integrity of building information models
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
151599 2018 14 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Automation in Construction, Volume 85, January 2018, Pages 249-262

پیش نمایش مقاله
پیش نمایش مقاله  منطق برای اطمینان از یکپارچگی مبادله داده ها از مدل های اطلاعات ساختمان

چکیده انگلیسی

Industry domains require distinct data and structures of building information models developed and tailored for their disciplines. To seamlessly exchange the building information models, Industry Foundation Classes (IFC), which is one of neutral formats, has been broadly used the architecture, engineering and construction, and facility management industries. Model views definitions (MVD), which is one of the IFC sub-schemas used by domain experts and BIM software vendors, consists of IFC-mapped data exchange requirements of each domain and helps software vendors develop IFC import and export features that allow project participants share and exchange BIM information. Because of the heterogeneous translation processes and structures of IFC interfaces according to model views, their validation is imperative to ensure the integrity of BIM data and maintain a consistent data exchange environment. To accomplish this objective, this paper suggests a new approach to evaluating BIM data in accordance with diverse requirements of MVD. Since MVD entails various types of data exchange specifications, this research examines their embedded checking rule types and categorizes corresponding implementation scenarios. In addition, this paper involves rule logic and IfcDoc-based BIM data validation developed based on the logical rule compositions of identified rules types and checking scenarios. This approach is expected to support sharing consistent BIM data sets and confirming the quality of received data pertaining to the syntax and semantics of a targeted model view.