Slope topographic effects on the nonlinear seismic behavior of groups of similar buildings
Bibliographic record
Abstract
Abstract The occurrence of vibrational energy exchange between neighboring buildings via soil is a well‐known issue today as structure‐soil‐structure interaction (SSSI) problems. Furthermore, the seismic performance of buildings near the slopes considering seismic topography‐soil‐structure interaction (TSSI) is entirely different from their performance on the flat grounds considering seismic soil‐structure interaction (SSI). Therefore, this study evaluates the seismic response of three moments resistant frame steel buildings with 15, 10, and 5 stories using three dimensional numerical analysis as a new topography‐structure‐soil‐structure interaction (TSSSI) problem. This issue has not been investigated in previous studies to the best of the authors' knowledge. In each case of TSSSI, two, three, and four buildings with similar dynamic properties were simulated simultaneously. The effects of foundation's rocking, numbers of buildings, and the 2D and 3D arrangements of buildings were investigated, and the results of TSSSI cases were compared with the corresponding SSSI cases. The inelastic behavior for both building components and soil was considered in the simulations. Analyzes are performed based on seven earthquake records from which the average value was taken as final results. Results show that it is essential to consider the TSSSI effect, and it can completely change the seismic performance of buildings near the slopes. Although the effects of TSSI and SSSI on the seismic responses of the low‐rise similar structures are negligible relative to the SSI cases, the results show that the nonlinear TSSSI effects of adjacent buildings should be fully considered even for 5‐story low‐rise structures.
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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 | 0.000 | 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 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".