Improving the Life Service of Fe-34Mn-10Al-0.76C Tidal Turbine Blades Using Variable PMF
Bibliographic record
Abstract
This paper studied the effect of increasing pulsed magnetic field (PMF) voltage during treating a Fe-34Mn-10Al-0.76C steel alloy used in fabricating a blade to be installed in a tidal turbine on its fatigue lifetime. Fatigue strength for each sample treated using PMF voltages (0, 100 and 160 V) had been investigated experimentally to plot their S-N curves while fatigue lifetime of the tidal turbine had been predicted using mathematical model established by a MATLAB code. The cyclic loadings affect the studied turbine were rearranged using Rainflow algorithm. Results of the study showed that, the blade made of Fe-34Mn-10Al-0.76C steel alloy and treated using PMF 100 v had achieved the highest fatigue resistance. The aforementioned fact had investigated based on comparing among the three specimens under the same conditions. For each specimen, the effect of the tidal turbine operation period according to fatigue lifetime been examined as well and it was investigated that, increasing number of operation hours resulted in a drastic reduction in the turbine’s fatigue life of the turbine.
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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 | 0.000 | 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) | 0.001 | 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".