For the mechanical analysis work in the structural design phase, data conversion and information transfer between BIM model and finite element model have become the main factors limiting its efficiency and quality, with the development of BIM (building information modeling) technology application in the whole life cycle. The combined application of BIM and ontology technology has promoted the automation of compliance checking, cost management, green building evaluation, and many other fields. Based on OpenBIM, this study combines IFC (Industry Foundation Classes) and the ontology system and proposes an automatic generation method for converting BIM to the finite element model. Firstly, the elements contained in the finite element model are generalized and the information set requirement, to be extracted or inferred from BIM for the generation of the finite element model, is obtained accordingly. Secondly, the information extraction technical route is constructed to satisfy the acquisition of the information set, including three main aspects, i.e., IFC-based material information, spatial information, and other basic information; ontology-based finite element cell selection method; and APDL statement generation methods based on JAVA, C#, etc. Finally, a complete technical route and a software architecture, designed for converting BIM to the finite element model, are derived. To assess the feasibility of the method, a simple structure is tested in this paper, and the result indicates that the automatic decision-making reasoning mechanism of constructing element type and meshing method can be explored by ontology and IFC. This study contributes to the body of knowledge by providing an efficient method for automatic generation of the BIM structure model and a reference for future applications using BIM in structural analysis.
In the architectural, engineering and construction (AEC) industry, manual compliance checking is labour-intensive, time-consuming, expensive and error-prone. Automated compliance checking (ACC) has been extensively studied in the past 50 years to improve the productivity and accuracy of the compliance checking process. While numerous ACC systems have been proposed, these systems can only deal with requirements that include quantitative metrics or specified properties. This leaves the remaining 53% of the building requirements to be checked manually, mainly due to the ambiguity embedded in them. In the literature, little is known about the ambiguity of building requirements, which impedes the accurate interpretation and automated checking of these requirements. This research thus aims to address this issue and establish a taxonomy of ambiguity. Building requirements in Health Building Notes (HBN) are analysed using an inductive approach. The results show that some ambiguous clauses in building requirements reflect regulators' intention, while others are unintentional, resulting from the use of language, tacit knowledge and ACC-specific reasons. This research is valuable for compliance-checking researchers and practitioners by unpacking ambiguity in building requirements, which lays a solid foundation to address ambiguity appropriately.
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