Tsunami Hazard Evaluation at Selected Locations Along the South Andhra Coast: Numerical Modeling and Field Observations
Bibliographic record
Abstract
Abstract The Andhra coast is well known for cyclones and less known for tsunamis. The December 26, 2004, Sumatran Indian Ocean tsunami, created considerable damages along the south Andhra coast, especially along the Krishnapatnam, Kavali, and Ongole coasts. Of these, Krsihnapatnam and Kavali were the most affected and have experienced run-up levels of 1.9 m and inundation distances of 200–1350 m. In places of straight coast, the tsunami run-up was limited to berm level (200–400 m from the shoreline) whereas in places occupied by creeks, inlets, and river mouths the run-up extended far inland up to 600–1350 m. The TUNAMI-N2 model simulations on propagation times, run-up, and inundation distances along Krishnapatnam, Kavali, and Ongole coasts are well agreed with the observed features of tsunami. The travel times of Sumatra 2004 tsunami to reach the shore along the three coasts are 175, 180, and 190 minutes, respectively, which are reproduced well in model simulations. Evaluation tsunami hazard levels along the three coastal sites are discussed in terms of run-up as most of the villages, public places, and shrimp culture ponds are located within 1–1.5 km of the shoreline. Keywords: Tsunami hazard evaluationtsunami signaturesTunami-N2 modeleast coast of India Acknowledgements The authors express their gratitude to Dr. Pary (L&T, Chennai), Dr. V. Ram Mohan (University of Madras), and P. Padmanabham (DRDO, Cochin) for their support in field surveys and data analyses. Notes *An hypothetical case of tsunami that occurred at Carnicobar with Sumatra 2004 earthquake source parameters.
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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 | 0.000 | 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 | 0.001 | 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) | 0.002 | 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".