Considerations for measuring residual stresses in driven piles with vibrating wire strain gauges
Bibliographic record
Abstract
Vibrating wire strain gauges are often the preferred technology for measuring strain in driven piles. However, measuring the residual strain after pile driving is challenging to accomplish using vibrating wire gauges. The driving process can cause a shift in the no-load reading from a relaxation of locked-in manufacturing strains in the pile or relaxation of the gauge wire tension. Also, there are temperature effects from installing piles below ground. A test pile program was developed using driven steel H-piles instrumented with vibrating wire strain gauges. The piles were subjected to dynamic forces by striking against a steel plate in an attempt to relax the locked-in manufacturing strain prior to installation. The strain gauges and thermistors were connected to a data logger during pile driving to record strain and temperature changes following installation. It was observed that applying a dynamic impact to the piles prior to installation resulted in a shift of 0–5 με (microstrain). Temperature effects from installing the piles in cooler ground resulted in a shift of strain in excess of 60 με in some strain gauges. It is concluded that temperature-induced shifts to strain must be measured following pile driving to interpret residual stresses.
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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 | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".