Numerical Modeling of Higher Mode Effects of Adjacent Tall Buildings on Seismic Response of a Tunnel
Bibliographic record
Abstract
In an urban area, during large earthquakes, a tall building will generate large base shear forces that may be transmitted into the underground structure through the building’s foundation and the surrounding soils. This study evaluates the impact of higher modes of the adjacent 13- and 42-degree of freedom (DOF) building models which represent 13-story midrise and 42-story high-rise buildings on the seismic response of the cut-and-cover tunnel in soil-superstructure-underground structure (SSUS) system using three-dimensional nonlinear finite element analysis. First, the seismic response of the tunnel adjacent to the equivalent 3-DOF midrise and 1-DOF high-rise models were compared to the corresponding centrifuge measurements, and good agreement was observed. Then, these calibrated numerical models are used to extend the building model into more realistic superstructure representation by including higher modes of the adjacent midrise and high-rise buildings. The results show that there is a significant increase in the spectral accelerations and base shear of the building due to the inclusion of the higher modes, which lead to the overall increase in dynamic earth pressure increments on the building-side wall of the tunnel. However, there are only small changes in the spectral accelerations and racking displacements on the tunnel wall. This study highlights that the seismic response of the building and tunnel might be underestimated if higher modes are ignored in the analysis.
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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 | 0.001 | 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".