Performance Assessment of Buildings Impacted by the 2019 Windstorm in the Central-South of Nepal
Bibliographic record
Abstract
The 2019 windstorm in Nepal struck villages in the Bara and Parsa districts, central-south of Nepal, on March 31, 2019, causing widespread devastation. The storm, rated five (5) on the Enhanced Fujita Scale, cut a 33 km swath through central-southern Nepal. In total, 1,452 private houses were destroyed, while 1,373 others suffered partial damage. The tragic storm claimed 28 lives and left 1,155 individuals injured. The impact of this tragedy extended to nearly 3,000 families. Immediately after the storm, a comprehensive damage assessment framework was developed, and a field reconnaissance study was conducted to understand the damage distribution and building failure mechanisms under tornado wind loads. Common damage modes observed were roofing material damage, roof-to-wall connection failure, and brittle masonry wall failures in the affected areas. This paper presents the lessons learned from damage to the building infrastructure during the 2019 windstorm in Nepal. Examined buildings underscore the critical need for design alternatives and sustainable retrofits, emphasizing load path integration and strong roof-to-wall connection. Strengthening the building envelope can significantly enhance its resilience against storms and other disasters prominent in the region. This study highlights the importance of proactive measures to safeguard vulnerable communities against natural hazards and offers insights into resilient building construction technology.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".