THE NUMERICAL AND EMPIRICAL EVALUATION OF STRUCTURAL PERFORMANCE OF ELEVATED TANKS CONSIDERING SOIL–STRUCTURE INTERACTION EFFECTS
Bibliographic record
Abstract
Water tanks are an essential lifeline whose continuing availability and serviceability immediately after earthquake events are crucial for providing undisrupted emergency services. Their seismic performance is, therefore, of paramount importance. The seismic response of an elevated liquid tank situated on a soft soil deposit was studied by means of field vibration tests and numerical simulations. The ambient and forced vibration tests were conducted to identify the soil–structure interaction (SSI) effects on the small strain dynamic behavior of the structure. A series of time domain numerical analyses were performed to evaluate the seismic performance of these structures from a performance based design point of view. The results showed that consideration of SSI increased the displacement demand significantly. Thus, the calculated maximum displacement demand for supporting frame components of the tank may be underestimated significantly when the SSI effects are neglected. In addition, the seismic induced shear forces considering SSI effects were much smaller than the seismic shear forces for the fixed based case. For some soil types, the effect of this reduction on the overall response may become more prominent than the structural ductility mechanism. This resulted in the failure mechanism being initiated by a coupled compression — bending moment effect, rather than shear failure. Finally, the sloshing response is significantly increased due to the SSI.
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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 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".