Protection of Critical Assets from Construction Vibration - Field Tests, Prediction, and Control
Bibliographic record
Abstract
This paper presents the results from vibration testing and modelling conducted during the design of a major hospital complex expansion adjacent to a research facility. The expansion will include demolition of existing structures at the site and construction of several multi-storey buildings. Foundation works will include construction of raft slabs and installation of Franki piles. The research facility houses sensitive laboratory equipment as well as a vivarium at basement level. Protection of research assets is a major concern during demolition and construction as ground-borne vibrations can affect performance of sensitive equipment, disrupt long-term experiments (e.g., cell culture development), and negatively impact the health of the animals. As Vibration Consultants on the project, the authors were responsible for developing vibration control specifications to ensure appropriate protection of the research facility (and surrounding land uses) during demolition and construction. This included development of a construction vibration model to predict vibration levels during various demolition and construction activities. Model parameters were specified based on coordinated testing at the site, which included: the use of an excavator armed with a plate compactor to apply impacts and vibratory compaction to the ground at the surface and at a depth corresponding approximately to the depth of foundations for the new buildings; and, Installation of two Franki piles at locations corresponding to new building foundations. During the tests, vibration levels were measured in the research facility and at various surface-level setbacks from the sources to quantify ground transmission characteristics and response of the structure. The results of all tests and models were applied for the development of vibration control measures that included a construction vibration control specification and monitoring protocol.
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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".