Microstructure Analysis and Finite Element Modelling for Creep Failure Prediction and Fitness-For-Service Assessment of Superheater Tubes
Bibliographic record
Abstract
Abstract This study aimed to perform a fitness-for-service assessment and investigate the root cause of failure of Grade 14CrMo3 steel seamless tubes typically used in superheaters in power generation plants. For this purpose, samples were taken from in-service superheater tubes in a 320 MW power plant. Thickness and hardness measurements were taken from the samples, and microstructural analyses were performed using scanning electron microscopy equipped with energy dispersive X-ray spectroscopy and X-ray diffraction. The results showed the presence of vanadium (V) and sulfur (S) elements on the tubes' external surface (flue gas facing-side), which is indicative of fuel ash corrosion. The formation of low melting point salts, such as Na2SO4, NaVO3, Na2O, and V2O5 (particularly between 10 and 2 o'clock positions) and degradation of the protective oxide layer led to loss of tube wall thickness. On the steam side of the tubes, the formation of an iron oxide layer (particularly between 12 and 2 o'clock positions) and the presence of water in the steam due to the improper function of the steam drum created an insulated zone leading to the formation of localized hot spots, creep microvoids, and spheroidization of carbides. In addition, a thickness reduction of 18% resulted in a considerable increase in hoop stresses having a detrimental effect on the remaining creep life. To explain the creep damage mechanism and determine the remaining creep life, the Larson–Miller criteria and API 579-1/ASME fitness-for-service-1 guidelines were utilized. The effects of the reduction in wall thickness were considered by performing a three-dimensional finite element analysis. The results showed that a temperature increase of only 50 °C (from 480 °C) could decrease the life of the tubes from 30 years to less than a year.
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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 | 0.001 | 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 | 0.000 |
| 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".