Torsional Irregularity Control in Irregular Plan RC Buildings through Optimized Shear Wall Placement: A Parametric Study
Bibliographic record
Abstract
Irregular buildings, particularly those with L-shaped plans, are more vulnerable during seismic events due to their asymmetric geometry and torsional irregularity. This study investigates the seismic performance of L-shaped reinforced concrete (RC) structures with various shear wall configurations under lateral loading. A total of 12 L-shaped six-story building models were analyzed using ETABS software, applying both Equivalent Static Method (ESM) and Response Spectrum Analysis (RSA) as per IS 1893:2016. The effect of shear wall positioning on fundamental time period, base shear, displacement, torsional irregularity and diaphragm rotation was evaluated. Results showed that shear walls significantly enhance structural performance by reducing displacement, increasing base shear, and controlling torsional behavior when placed effectively. Improper or asymmetric wall placement, however, led to increased torsional amplification and irregular seismic responses. Among all models, those with shear walls aligned along both X and Y directions performed best in terms of seismic resistance. The study highlights the importance of optimal shear wall positioning in irregular RC buildings for enhancing seismic safety and structural efficiency.
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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 | 0.001 |
| 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) | 0.001 | 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".