Modeling of lightly reinforced concrete walls subjected to near‐fault and far‐field earthquake ground motions
Bibliographic record
Abstract
Abstract Reinforced concrete bearing walls with low vertical reinforcement ratios of less than 0·2% are referred to as lightly reinforced walls. Recently, Eurocode 8 and the French code PS 92 adopted a special design concept for lightly reinforced concrete walls based on the multifuse principle favouring rupture occurrence at several storeys. This design leads to lower reinforcement ratios with their optimized distribution allowing wide cracks to take place with large energy dissipation potential. In addition, the vertical displacement of the mass results in energy transformation from kinematic to potential. The objective of the investigation is to analytically predict the response of such lightly reinforced walls when subjected to near‐fault and far‐field ground motion records up to failure to establish the load‐carrying capacity and ductility of the walls. A wall was modeled using six‐node two‐dimensional panel elements. The panel elements have lumped flexural/axial plasticity at their top and bottom fibre sections. The response of the wall was evaluated in terms of pushover, spectral, displacement‐based, and time history analyses. The model and the response data were verified against available measurements from a test program conducted using a shake table. The comparison indicated that the model closely represented the behaviour observed in the test. Copyright © 2007 John Wiley & Sons, Ltd.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".