Design Principles for Earthquake Resistant Buildings and Post Earthquake Study by Structural Engineering Perspectives
Bibliographic record
Abstract
Two major earthquakes hit India in last eight years. The first in Killari \n(Latur) Maharashtra on 30th September 1993(Magnitude 6.4,deaths \nabout 10,000) and the second recently at Bhuj Gujrat on 26th January \n2001(Magnitude 8.1,deaths more than 35000).In USA two earthquakes \ntook place one in California on 17th January 1994(Magnitude \n6.6,deaths 57) and second in Ciatel near Canada on 1 \nst March \n2001(Magnitude 6.8,death 1).It shows clearly that the damage to \nstructures and loss of life is more in developing countries like India as \ncompared to developed countries like USA,Japan etc. This is due to lack \nof awareness in adopting Indian Standard codal provisions for \nearthquake resistant design. It is highly expensive to construct \nstructure 100% earthquake proof. This paper aims to highlight design \nprinciples for earthquake resistant buildings which should be \ncompulsorily adopted during the construction. In this paper, post \nearthquake effects on buildings from structural point of view are also highlighted.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 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 teacher head, 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".