UBC Theses and Dissertations
Automated extraction and querying of construction-specific design features from a building information model Nepal, Madhav Prasad
In recent years, several research and industry efforts have focused on developing building information models (BIMs) to support various aspects of the architectural, engineering, construction and facility management (AEC/FM) industry. BIMs provide semantically-rich information models that explicitly represent both 3D geometric and non-geometric information. While BIMs have many useful applications to the construction industry, there are enormous challenges in getting construction-specific information out of BIMs, limiting the usability of these models. This research addresses this problem by developing a novel approach to extract construction features from a given BIM and support the processing of user-driven queries on a BIM. In this dissertation, we formalized: (i) An ontology of design features that explicitly represents design conditions that are relevant to construction practitioners and supports the generation of a construction-specific feature-based model; (ii) A query specification vocabulary which characterizes spatial and non-spatial queries, and developed query templates to guide non-expert BIM users to specify queries; and (iii) An integrated approach that combines model-based reasoning and query-based approach to automatically extract design features to create a project-specific feature-based model (FBM) and provide support for answering queries on the FBM. The construction knowledge formalized in this research was gathered from a variety of sources, which included a detailed literature review, several case studies, extensive observations of design and construction meetings, and lengthy discussions with different construction practitioners. We used three different tests to validate the research contributions. We conducted semi-structured, informal interviews with four construction experts for the four building projects studied to validate the content, representativeness and the generality of the concepts formalized in this research. We conducted retrospective analysis for different features to evaluate the soundness of our research in comparison with the state-of-the-art tools. Finally, we performed descriptive and interpretive analysis to demonstrate that our approach is capable of providing richer, insightful and useful construction information. This research can help to make a BIM more accessible for construction users. The developed solutions can support decision making in a variety of construction management functions, such as cost estimating, construction planning, execution and coordination, purchasing, constructability analysis, methods selection, and productivity analysis.
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