Ontology-Based Design Features for Representing Constructability in Architectural Design: Toward BIM in Off-Site Construction
Bibliographic record
Abstract
To enable off-site construction (OSC), architects must finalize construction details in their design deliverables as early as possible, particularly in a building information modeling (BIM) environment, to enhance design constructability and project efficiency. However, most architects lack construction knowledge and practical experience, which impedes their ability to incorporate design-specific construction input (i.e., manufacturing, logistics, assembly, and installation demands) into BIM processes at the early stages. This deficiency can lead to errors, rework, and ultimately increased construction costs. To address this challenge, this study introduces an innovative approach to incorporate constructability knowledge into architectural design processes for BIM-enabled OSC projects. The methodology involved retrospective case studies of two completed OSC projects utilizing a component-centric analysis framework. This analysis resulted in an ontology of construction-specific design features that identified 11 types of constructability issues and the characterization of nine design feature classes that were categorized into three groups: substance; intersection; and composition. These feature classes and their 29 attributes were rigorously characterized from the perspective of BIM-enabled architectural design. This feature-based approach not only extends the BIM vocabulary and semantics from an architectural standpoint but also encapsulates construction knowledge as an integral input to architectural design. Additionally, three strategies were identified, analyzed, and summarized to inform these design features and attributes and to evaluate their effectiveness of addressing constructability issues. The study’s ontological approach assists architects in acquiring a comprehensive understanding of design-specific construction knowledge, enabling them to differentiate, locate, and integrate critical types of constructability information into BIM-enabled architectural design deliverables early in the project delivery process. This paper is a foundational step in the development of automated modeling, algorithms, and constructability assessment for BIM-enabled architectural design deliverables, aimed at achieving a more streamlined construction process.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".