A Macro‐Distinct Element Model (M‐DEM) for simulating in‐plane/out‐of‐plane interaction and combined failure mechanisms of unreinforced masonry structures
Bibliographic record
Abstract
Abstract In the seismic analysis of unreinforced masonry (URM) structures, the modeling of out‐of‐plane (OOP) modes and their mechanical interaction with in‐plane (IP) loaded components are typically neglected when using simplified numerical methods. Although this may result in unconservative predictions, the high computational expense entailed by more refined approaches is often prohibitive for applied researchers and practitioners. To overcome these limitations, the demonstrated capabilities of a recently developed low‐cost Macro‐Distinct Element Model (M‐DEM) to simulate IP and OOP modes are extended in this work towards the modeling of IP/OOP interaction and combined failure mechanisms of URM assemblies. In the M‐DEM framework, shear and flexural damage are accounted for by zero‐thickness interface spring layers, whose layout is determined a priori as a function of the masonry texture, while crushing failure is modeled through homogenized finite element macro‐blocks. To adapt and validate this M‐DEM scheme to model IP/OOP interaction, past experiments on full‐scale C‐, U‐, and I‐shaped URM specimens tested under quasi‐static loading were simulated. The shake‐table response of a full‐scale C‐shaped URM assembly with openings was also numerically simulated up to collapse, representing a major improvement over previous macro‐element methods. After the comparison with experimental tests, a parametric investigation of the response of reference URM walls under combined IP/OOP actions was conducted, and the influence of previous IP damage on one‐ and two‐way OOP bending capacity is quantified. This aspect, despite being widely identified as of relevant interest, has only been marginally investigated in previous research, both experimentally and numerically.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".