Simplified structural analysis framework for buildings under combined earthquake and tsunami loads
Bibliographic record
Abstract
In recent years, several catastrophic tsunami events have captured the attention of researchers, leading to studies on the structural behaviour of buildings subjected to tsunami loads to develop efficient and practical prevention systems. International building codes and design standards have reacted by providing innovative approaches to design tsunami-resistant structures; however, analysis approaches that consider potential earthquake damage prior to the loading imposed by the tsunami are lacking. This paper aims to assess the global structural behaviour of reinforced concrete buildings subjected to earthquake damage and tsunami loading considering both in-plane and out-of-plane behaviour of infill walls on the global structural response of RC buildings. A structural analysis framework is proposed to assess the capacity of prototype buildings under tsunami loading following previous seismic-induced structural damage that is classified based on specific damage states. The procedure is based on nonlinear static pushover analysis. Analyses are performed on two different building models representing new construction and an old existing structure. This study focuses on critical aspects regarding the structural modelling and analysis. Specifically, recommendations are provided on modelling the behaviour of infill walls related to in-plane and out-of-plane local mechanisms due to its influence on the global structural behaviour. The new building provides an enhanced response over the existing building due to a more efficient design approach. Furthermore, tsunami analysis is dependent mainly on the strength capacity of the elements directly inundated, while seismic analysis involves the entire structure. The modelling of the infill walls in the structural models increases the stiffness and represents a critical element for the loading of the structure. Structural collapse during the analysis is mainly controlled by shear failure in the columns at the ground floor level.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".