Metallurgical and Fracture Toughness Variability Characterization of 2.25Cr 1 Mo Plate Steel for Hydroprocessing Reactors
Bibliographic record
Abstract
Abstract Fracture toughness and temper embrittlement susceptibility are pivotal factors influencing the mechanical integrity of hydroprocessing reactors within oil refineries and chemical plants. Moreover, they exert a notable impact on the minimum allowed pressurization temperature (MPT), thereby affecting the startup and shutdown times. Enhanced fracture toughness at low temperatures and heightened resistance to temper embrittlement lead to a lower permissible MPT setting. Temper-embrittlement is the reduction in fracture toughness due to a metallurgical change that can occur in some low-alloy steels as a result of prolonged exposure in the temperature range of about 650 °F to 1070 °F (345 °C to 575 °C). This change causes an upward shift in the ductile-to-brittle transition. Although the loss of toughness is not evident at operating temperature, equipment afflicted by temper embrittlement becomes susceptible to brittle fracture during start-up and shutdown processes. This paper includes a literature review and describes the variability in fracture toughness of 2.25Cr 1Mo steel plate material as a function of temperature. Additionally, it presents a case history where high variability was reported in weld deposits. Factors affecting fracture toughness and tempering embrittlement are analyzed and recommendations to maximize fracture toughness and reduce temper embrittlement susceptibility are included. Finally, the paper touches upon technology limitations as dictated by contemporary manufacturing practices. The characterization process incorporates optical microscopy, scanning electron microscopy, hardness, chemistry, impact testing and crack tip opening displacement measurements.
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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".