Nonlinear Seismic Assessment of a Historic Rubble Masonry Building via Simplified and Advanced Computational Approaches
Why this work is in the frame
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Bibliographic record
Abstract
This research presents a comprehensive nonlinear quasi-static seismic assessment of an unreinforced rubble masonry building, Bytown Museum in Ottawa, Canada, using discontinuum-based analyses. In the proposed modeling approach, non-uniform geometrical properties of rubble masonry walls are replicated via a group of rigid polyhedral blocks interacting along their boundaries based on the discrete element method (DEM). Once the adopted modeling strategy is validated, the nonlinear quasi-static analysis of the South and North façades of the Bytown Museum is performed. Special attention is given to the irregular block generation within the discontinuum analysis framework, where discrete element models are generated from high-resolution site recording data, representing the masonry morphology at a high level of detail. Then, the predicted collapse mechanisms from advanced computational models are further utilized to generate pre-defined macro-blocks in kinematic limit analyses, providing a simple alternative solution for seismic assessment. The results reveal the significant effect of openings and the construction technique (morphology) in unreinforced rubble masonry buildings that can play an important role in the structural capacity and behavior. Moreover, it is noted that DEM-based solutions provide lower seismic capacity compared to kinematic limit analyses. Finally, a noticeable sensitivity to the input parameters in the discrete element models is noted; therefore, characterization of material properties is necessary for reliable predictions.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 it