Austenite Grain Size Model for the Coarse Grain Heat Affected Zone in Line Pipe Steels
Bibliographic record
Abstract
Abstract Pipelines are the safest and most cost-effective method of oil and gas transportation to storage and processing facilities. Large diameter welded pipes fabricated by submerged arc welding (SAW) are the preferred product in many cases for pipeline construction. Furthermore, pipelines are constructed by welding segments of pipe, typically by single or dual torch Gas Metal Arc Welding (GMAW). During welding, both during pipe fabrication and girth welding, the Heat Affected Zone (HAZ) experiences rapid thermal cycles with peak temperatures up to the melting temperature of the base metal. Controlling the microstructure evolution in the HAZ during welding of line pipe steels is critical to ensure that these products meet the Charpy impact testing and CTOD requirements imposed by clients and specifications. In particular, the Coarse Grain Heat Affected Zone (CGHAZ) is of concern. Here, austenite grain growth occurs readily due to the combination of high temperature and precipitate dissolution. Controlling the CGHAZ austenite grain size is critical to obtain final microstructures with acceptable impact properties. In this study, austenite grain growth has been measured and modeled for thermal conditions relevant for the CGHAZ in 27 steels, including industrial as well as laboratory steels with systematic variations of alloying element content. Austenite grain size was measured using a Laser Ultrasonics for Metallurgy (LUMet) sensor attached to a Gleeble 3500 Thermomechanical Simulator, which enables high-throughput in-situ monitoring of austenite grain growth. A classical grain growth model has been developed based on a standard test. The grain growth kinetics are described by combining curvature driven grain growth with pinning due to TiN precipitates. A phenomenological relationship has been developed for the grain boundary mobility that decreases with C, Nb and Mo alloying which is consistent with their expected grain boundary segregation. The pinning parameter is rationalized in terms of volume fraction and size of TiN particles. The proposed model has been validated for CGHAZ heat treatment cycles including an industrial welding trial. The results of this study provide a model to predict the austenite grain size in the CGHAZ as a function of steel chemistries and heat treatment paths, i.e. welding parameters. Austenite grain size maps have been constructed as a function of peak local temperature and line pipe steel chemistry. The model can be used both for steel chemistry design and for optimizing welding of steels with known chemical composition to minimize the CGHAZ austenite grain size both during pipe fabrication and girth welding.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".