Engineering Lessons from September 28, 2018 Indonesian Tsunami: Scouring Mechanisms and Effects on Infrastructure
Bibliographic record
Abstract
The September 28, 2018 earthquake and tsunami, which occurred north of Palu City, Indonesia, attracted widespread interest from the scientific community due to the unusually large tsunami that occurred after a strike-slip earthquake with a relatively small moment magnitude (MW = 7.5). To understand the structural performance of buildings and infrastructure under hydrodynamic loads and their associated effects, the authors conducted field surveys in Palu City. Light wooden frame constructions and masonry infill walls were common in the area, some of which were severely damaged by the earthquake and tsunami. Reinforced concrete structures remained predominantly intact, although they suffered soil-related issues such as scour around rigid building members. Local structural failures caused by the loss of supporting soil were also observed during the field survey, resulting in an overall reduction in the stability of the inspected structures. Based on the observations made, knowledge gaps and research needs concerning coastal and structural scouring are discussed. These are tied into the latest community research activities and put in the context of a published ASCE standard chapter that discusses tsunami design.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".