Application de la méthode d'émission acoustique pour la surveillance du comportement au cisaillement des joints actifs
Bibliographic record
Abstract
A key requirement in evaluation of sliding stability of concrete dams is monitoring shear behavior of 1) concrete joints in dam body, 2) concrete-rock interfaces and 3) rock discontinuities in dam foundation. The methodology consisted of creating a database of observed shear behaviors of the mentioned joints using acoustic emission (AE) technique. Joint samples were fabricated by tension splitting of the cores and pouring concrete on rock joint replica for simulating concrete-rock interfaces. Variations of key parameters including joint geometry, normal stress, displacement rate and bonding percentage were incorporated in the analysis. An analysis was also carried out on natural joints from Daniel Johnson (Manic 5) Dam, Quebec, founded on gneiss to granitic rock. Parametric-based and signal-based analysis methods were used to evaluate the potential of AE for monitoring shear behavior of various kinds of joint with different characteristics. Using AE parameters such as amplitude, count, energy, duration and rise time, this study was done as a feasibility study for AE monitoring of sliding surfaces within dam, dam-rock interface or inside rock foundation. It was found that AE has a good capability for showing the initial shear movement of the non-bonded joints. For bonded joints this technique can show that AE activities are occurring before breaking of adhesive bond. This is important because recording AE signals after an initial breakage of the joint would be too late to install stabilization work to be done beforehand. Of course in the eventuality that a rupture includes a sequence of events even recording AE signals of the first break is still useful. It is recommended to use this method combined with other instrumentation methods (e.g. load measuring instruments) to detect the initial shear movement of the bonded joints. Following experimental work and analysis of crack propagation and asperity degradation along shearing process, four different periods were observed in shear stress-displacement behavior of joints. These periods are: 1) Pre-peak linear period in which AE activities are initiated and show the beginning of shear displacement, 2) Pre-peak non-linear period in which AE signals are generated from crack initiation and degradation of the secondary asperities, 3) Post-peak period where first order asperities are sheared off and joints pass their maximum shear strength and 4) Residual period in which AE activities decrease and reach their minimum values. The applicability. of AE localization technique was evaluated using image analysis and scanned surfaces of the joints by laser. The results indicated that this method can locate regions with rupture governing characteristics. This provides the possibility to reinforce support systems and be aware about possible structure failures before any unexpected mechanical disturbance.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".