Capability of Advanced Ultrasonic Inspection Technologies for Hydraulic Turbine Runners
Bibliographic record
Abstract
This paper presents the results of a project aimed at evaluating the performance of ultrasonic techniques for detecting flaws in Francis turbine runners. This work is the first phase of a more ambitious program aimed at improving the reliability of inspection of critical areas in turbine runners. Francis runners may be utilized to supply power during peak periods, which means that they experience additional load stress associated with start and stop sequences. Inspection during manufacturing is then of paramount importance to remove as much as feasible all flaw initiation sites before the heat treatment. This phase one objective is to collect initial data on a simplified mock-up and then to compare the experimental ultrasonic data with the results of simulations performed by CIVA, a computer simulation package. The area of interest is the region with the highest stress between the blade and the web. A welded T-joint coupon made of UNS S41500 was manufactured to represent this high-stress area. During the FCAW welding process, ceramic beads were embedded in the weld to create discontinuities whose size is in the critical range to initiate a crack. Inspection of the material was carried out by various nondestructive testing (NDT) methods namely conventional pulse-echo, phased array, total focusing method (TFM). With these results, detection rates were obtained in order to compare the effectiveness of each method.
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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".