Subway train-induced noise and vibration in buildings: predictions and measurements
Bibliographic record
Abstract
Urbanization ensures that noise and vibration from rail and metro lines will continue to be an important field of research as structures coexist with nearby rail lines. The transmission of train-induced noise and vibration through building remains an active field of research. This ongoing research is largely due to the complexity of modelling the transmission of broadband vibration through the soil, into the building’s foundation, and within the building itself. There are numerous approximate methods, empirically-derived models, and detailed finite-element approaches available to predict train-induced vibration levels within buildings; however, the uncertainty associated with these predictions remain large, and few have been extensively evaluating with measurements. The current study investigates the transmission of noise and vibration in a 17-storey reinforced concrete building located adjacent to the Toronto Transit Commission (TTC) Bloor-Danforth (Line 2) and Yonge-University (Line 1) lines. Vibrations are measured on the building’s foundation adjacent to the metro lines, and simultaneously, noise and vibration levels are measured on three elevated floors. Several dozen train passes are recorded over a measurement period of a few hours, and they are observed to be the dominant source of noise and vibration within the building. In this paper, the results of the measurement program are presented, and are compared to simple rail vibration and noise prediction methodologies. These measurements add to the limited but growing body of published in-situ measurement data that is necessary to evaluate predictive models for train-induced vibrations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".