Apparent wave velocity inverse analysis method and its application in dynamic pile testing
Bibliographic record
Abstract
Abstract This study proposes a new non‐destructive testing method (NDT), namely the apparent wave velocity of piles (AWVP) inverse analysis method, to solve the detection problem of the gradually varying cross‐sectional defects (cracks or necking) and the material property defects (concrete disintegration or steel corrosion) of piles. The analytical solution of the AWVP has been derived based on the additional mass model. The rationality and accuracy of the theoretical model have been validated through the comparisons with the experiment results. The variation mechanism of the AWVP due to the presence of soil has been clarified. A parametric study is conducted to investigate the major factors to determine the variation tendency of the AWVP. The optimum working conditions and parameter combinations of the AWVP based NDT method have been recommend. The main conclusions can be drawn as: (1) the variation of the AWVP with respect to frequency can be generally divided into a sensitive zone and a stable zone. (2) The AWVP initially decreases rapidly with the frequency within the sensitive zone, however when the frequency decreases to the stable zone, this decline tendency becomes much smaller. (3) Although the AWVP varies extensively within the frequency sensitive zone, this frequency range can substantially relax the requirements for the parametric accuracy of the pile–soil system.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".