Enhancing shear capacity of masonry wallet using PP-band and steel wire mesh
Bibliographic record
Abstract
Past earthquakes witnessed the poor performance of unreinforced masonry (URM) structures resulting into huge economic loss and large number of casualties. In this context, the present paper is aimed to investigate the shear behaviour of a series of masonry wallets (unretrofitted and retrofitted) under diagonal compressive loading. To improve the wallet behaviour in shear, polypropylene band (PP-band) and steel wire mesh (WM) are used as retrofitting material. Both faces of wall are wrapped to get full tightening effect during loading. Bricks having standard size and half scale size are used to construct the full scale wallet and small scale wallet, respectively. It has been observed that retrofitted wall exhibits significant improvement in terms of load carrying capacity, displacement ability. Failure mode for both unreinforced masonry (URM) and strengthened specimens are reported and shear strength is computed using analytical formulations. It was observed that both the strengthening materials not only increase the load carrying capacity but also helps in changing the failure mode from brittle to ductile in some extent. From the study, it may be concluded that use of PP band and steel wire mesh are effective in improving the shear behaviour of masonry structures for both the types of wallets.
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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 | 0.000 |
| 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) | 0.001 | 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".